@article{ribeiro_machine_2024, title = {Machine learning-based cardiac activity non-linear analysis for discriminating {COVID}-19 patients with different degrees of severity}, volume = {87}, issn = {1746-8094}, url = {https://www.sciencedirect.com/science/article/pii/S1746809423009916}, doi = {10.1016/j.bspc.2023.105558}, abstract = {Objective: This study highlights the potential of an Electrocardiogram (ECG) as a powerful tool for early diagnosis of COVID-19 in critically ill patients with limited access to CT–Scan rooms. Methods: In this investigation, 3 categories of patient status were considered: Low, Moderate, and Severe. For each patient, 2 different body positions have been used to collect 2 ECG signals. Then, from each collected signal, 10 non-linear features (Energy, Approximate Entropy, Logarithmic Entropy, Shannon Entropy, Hurst Exponent, Lyapunov Exponent, Higuchi Fractal Dimension, Katz Fractal Dimension, Correlation Dimension and Detrended Fluctuation Analysis) were extracted every 1s ECG time-series length to serve as entries for 19 Machine learning classifiers within a leave-one-out cross-validation procedure. Four different classification scenarios were tested: Low vs. Moderate, Low vs. Severe, Moderate vs. Severe and one Multi-class comparison (All vs. All). Results: The classification report results were: (1) Low vs. Moderate - 100\% of Accuracy and 100\% of F1–Score; (2) Low vs. Severe - Accuracy of 91.67\% and an F1–Score of 94.92\%; (3) Moderate vs. Severe - Accuracy of 94.12\% and an F1–Score of 96.43\%; and (4) All vs All - 78.57\% of Accuracy and 84.75\% of F1–Score. Conclusion: The results indicate that the applied methodology could be considered a good tool for distinguishing COVID-19’s different severity stages using ECG signals. Significance: The findings highlight the potential of ECG as a fast and effective tool for COVID-19 examination. In comparison to previous studies using the same database, this study shows a 7.57\% improvement in diagnostic accuracy for the All vs All comparison.}, urldate = {2024-01-14}, journal = {Biomedical Signal Processing and Control}, author = {Ribeiro, Pedro and Marques, João Alexandre Lobo and Pordeus, Daniel and Zacarias, Laíla and Leite, Camila Ferreira and Sobreira-Neto, Manoel Alves and Peixoto, Arnaldo Aires and de Oliveira, Adriel and Madeiro, João Paulo do Vale and Rodrigues, Pedro Miguel}, month = jan, year = {2024}, keywords = {Accuracy, COVID-19, ECG signals, Machine learning classifiers, Non-linear analysis, –}, pages = {105558}, } @article{lai_aspects_2024, title = {Aspects that constitute citizens’ trust in e-government - {A} review and framework development}, volume = {7}, issn = {2595-3982}, url = {https://malque.pub/ojs/index.php/mr/article/view/1591}, doi = {10.31893/multirev.2024023}, abstract = {The extent of citizens' trust in government determines the success or failure of e-government initiatives. Nevertheless, the idiosyncrasies of the concept and the broad spectrum of its approach still present relevant challenges. This work presents a systematic literature review on e-government trust while elaborating and summarizing a conceptual analysis of trust, introducing evaluation methods for government trust, and compiling relevant research on e-government trust and intentional behavior. A total of 26 key factors that constitute trust have been identified and classified into six categories: Government trust, Trust in Internet and technology (TiIT), Trust in e-government (TiEG), Personal Beliefs, Trustworthiness, and Trust of intermediary (ToI). The value added of this work consists of developing a conceptual framework of TiEG to provide a significant reference for future in-depth studies and research on e-government trust.}, language = {en}, number = {2}, urldate = {2024-01-14}, journal = {Multidisciplinary Reviews}, author = {Lai, Chimeng and Marques, Alexandre Joao Lobo}, year = {2024}, keywords = {Systematic Literature Review (SLR), framework, trust, trust in e-government}, pages = {2024023--2024023}, } @article{diakite_categorization_2023, title = {Categorization of {Foreign} {Aid} {Donors}: {A} {Critical} {Review} of the {Criteria} in {Light} of {China}'s {Reemergence} as a {Donor}}, volume = {40}, copyright = {Copyright (c) 2023 Association of Global South Studies}, issn = {2476-1419}, shorttitle = {Categorization of {Foreign} {Aid} {Donors}}, url = {https://journals.upress.ufl.edu/JGSS/article/view/2381}, abstract = {Over the past several decades, the dichotomy between traditional and emerging donors has been based upon the notion that emerging donors (such as China) support authoritarian regimes and use foreign aid to pursue their economic interests at the expense of the poor in the recipient countries. Accordingly, Western donors, media, and scholars portray Chinese aid as non-poverty-focused. This study aims to review and analyze whether the dichotomy between traditional and emerging donors is still relevant in the current aid system and to propose a new and rigorous criterion for recategorizing donors. In terms of methodology, this study relies on secondary data, including scholarly works on traditional and emerging donors and foreign aid policy documents. Conclusions based on the research indicate that the divide between traditional donors and (re)emerging donors is becoming more ambiguous. The literature review indicates that the two donors’ aids had a mixed impact and that their approaches were similar. This paper highlights the importance of developing different recategorization criteria depending on the impact of aid.}, language = {en}, number = {2}, urldate = {2023-12-18}, journal = {Journal of Global South Studies}, author = {Diakite, Ansoumane Douty and Marques, João Alexandre Lobo}, month = dec, year = {2023}, note = {Number: 2}, keywords = {China and development assistance committee donors, aid policies, categorization of donors, sustainable development goal, traditional and emerging donors}, } @article{hsu_neurofinance_2023, title = {Neurofinance: {Exploratory} {Analysis} {Stock} {Trader}'s {Decision}-{Making} {Process} by {Real}-{Time} {Monitoring} of {Emotional} {Reactions}}, volume = {19}, copyright = {Copyright (c) 2023 European Conference on Management Leadership and Governance}, issn = {2048-903X}, shorttitle = {Neurofinance}, url = {https://papers.academic-conferences.org/index.php/ecmlg/article/view/1692}, doi = {10.34190/ecmlg.19.1.1692}, abstract = {Human emotions can be associated with decision-making, and emotions can generate behaviors. Due to the fact that it could be biased and exhaustively complex to examine how human beings make choices, it is necessary to consider relevant groups of study, such as stock traders and non-traders in finance. This work aims to analyze the connection between emotions and the decision-making process of investors and non-investors submitted to the same set of stimuli to understand how emotional arousal might dictate the decision process. Neuroscience monitoring tools such as Real-Time Facial Expression Analysis (AFFDEX), Eye-Tracking, and Galvanic Skin Response (GSR) were adopted to monitor the related experiments of this paper and its accompanying analysis process. Thirty-seven participants attended the study, 24 were classified as stock traders, and 13 were non-traders; the mean age for the groups was 35 and 25, respectively. The designed experiment initially disclosed a thought-provoking result between the two groups under the certainty and risk-seeking prospect theory; there were more risk-takers among non-investors at 75\%, while investors were inclined toward certainty at 79.17\%. The implication could be that the non-investing individuals were less complex in thought and therefore pursued higher returns besides a high probability of losing the game. In addition, the automatic emotion classification system indicates that when non-investors confronted a stock trending chart beyond their acquaintance or knowledge, they were psychologically exposed to fear, anger, sadness, and surprise.\ On the contrary, investors were detected with disgust, joy, contempt, engagement, sadness, and surprise, where sadness and surprise overlapped in both parties. Under time pressure conditions, 54.05\% of investors or non-investors tend to make decisions after the peak(s) of emotional arousal. Variations were found in the deciding points of the slopes: 2.70\% were decided right after the peak(s), 37.84\% waited until the emotions turned stable, and 13.51\% were determined as the emotional indicators started to slide downwards. Several combinations of emotional responses were associated with decisions. For example, negative emotions could induce passive decision-making, in this case, to sell the stock; nevertheless, it was also examined that as the slope slipped downwards to a particular horizontal point, the individuals became more optimistic and selected the "BUY" option. Future works may consider expanding the study to larger sample size, different demographic groups, and other biometrics for further analysis and conclusions.}, language = {en}, number = {1}, urldate = {2023-12-18}, journal = {European Conference on Management Leadership and Governance}, author = {Hsu, Hsin-Tzu and Marques, João Alexandre Lobo}, month = nov, year = {2023}, note = {Number: 1}, pages = {147--155}, } @article{marques_leadership_2023, title = {Leadership and {Neurosciences} - {The} analysis of emotional arousal during decision-making processes with decision-makers exposed to acute stress}, volume = {19}, copyright = {Copyright (c) 2023 European Conference on Management Leadership and Governance}, issn = {2048-903X}, url = {https://papers.academic-conferences.org/index.php/ecmlg/article/view/1950}, doi = {10.34190/ecmlg.19.1.1950}, abstract = {Corporate leaders are constantly dealing with stress in parallel with continuous decision-making processes. The impact of acute stress on decision-making activities is a relevant area of study to evaluate the impact of the decisions made, and create tools and mechanisms to cope with the inevitable exposure to stress and better manage its impact. The intersection of leadership and neurosciences techniques is called Neuroleadership. In this work, an experiment is proposed to detect and measure the emotional arousal of two groups of business professionals, divided into two groups. The first one is the intervention/stress group, n=30, exposed to stressful conditions, and the control group, n=14, not exposed to stress. The participants are submitted to a sequence of computerized stimuli, such as watching videos, answering survey questions, and making decisions in a realistic office environment. The Galvanic Skin Response (GSR) biosensor monitors emotional arousal in real-time. The experiment design implemented stressors such as visual effects, defacement, unfairness, and time-constraint for the intervention group, followed by decision-making tasks. The results indicate that emotional arousal was statistically significantly higher for the intervention/stress group, considering Shapiro and Mann-Whitney tests. The work indicates that GSR is a reliable stress detector and may be useful to predict negative impacts on executive professionals during decision-making activities.}, language = {en}, number = {1}, urldate = {2023-12-18}, journal = {European Conference on Management Leadership and Governance}, author = {Marques, Joao Alexandre Lobo}, month = nov, year = {2023}, note = {Number: 1}, pages = {232--239}, } @article{zeng_neuromarketing_2023, title = {Neuromarketing: {Evaluating} {Consumer} {Emotions} and {Preferences} to {Improve} {Business} {Marketing} {Management}}, volume = {19}, copyright = {Copyright (c) 2023 European Conference on Management Leadership and Governance}, issn = {2048-903X}, shorttitle = {Neuromarketing}, url = {https://papers.academic-conferences.org/index.php/ecmlg/article/view/1876}, doi = {10.34190/ecmlg.19.1.1876}, abstract = {The invention of neuroscience has benefited medical practitioners and businesses in improving their management and leadership. Neuromarketing, a field that combines neuroscience and marketing, helps businesses understand consumer behaviour and how they respond to advertising stimuli. This study aims to investigate the consumer purchase intention and preferences to improve the marketing management of the brand, based on neuroscientific tools such as emotional arousal using Galvanic Skin Response (GSR) sensors, eye-tracking, and emotion analysis through facial expressions classification. The stimuli for the experiment are two advertisement videos from the Macau tea brand “Guanding Teahouse” followed by a survey. The experiment was conducted on 40 participants. 76.2\% of participants that chose the same product in the first survey responded with the same choice of products in the second survey. The GSR peaks in video ad 1 measured a total of 60. On the other hand, video ad 2 counted a total of 55 GSR peaks. The emotions in ad1 and ad2 have similar responses, with an attention percentage of 76\%. The results showed that ad1 has a higher engagement time of 11.1\% and ad2 has 9.6\%, but only 19 of the respondent’s conducted engagement in video ad1, and 31 showed engagement in video ad2. The results demonstrated that although ad 1 has higher engagement rates, the respondents are more attracted to video ad 2. Therefore, ad2 has better marketing power than ad 1. Overall, this study bridges the gap of no previous research on measuring tea brand advertisements with the neuroscientific method. The results provide valuable insights for marketers to develop better advertisements and marketing campaigns and understand consumer preferences by personalising and targeting advertisements based on consumers' emotional responses and behaviour of consumers' purchase intentions. Future research could explore advertisements targeting different demographics.}, language = {en}, number = {1}, urldate = {2023-12-18}, journal = {European Conference on Management Leadership and Governance}, author = {Zeng, Ian Mei and Marques, João Alexandre Lobo}, month = nov, year = {2023}, note = {Number: 1}, pages = {436--444}, } @article{rodrigues_enhancing_2023, title = {Enhancing {Health} and {Public} {Health} through {Machine} {Learning}: {Decision} {Support} for {Smarter} {Choices}}, volume = {10}, copyright = {http://creativecommons.org/licenses/by/3.0/}, issn = {2306-5354}, shorttitle = {Enhancing {Health} and {Public} {Health} through {Machine} {Learning}}, url = {https://www.mdpi.com/2306-5354/10/7/792}, doi = {10.3390/bioengineering10070792}, abstract = {In recent years, the integration of Machine Learning (ML) techniques in the field of healthcare and public health has emerged as a powerful tool for improving decision-making processes [...]}, language = {en}, number = {7}, urldate = {2023-08-01}, journal = {Bioengineering}, author = {Rodrigues, Pedro Miguel and Madeiro, João Paulo and Marques, João Alexandre Lobo}, month = jul, year = {2023}, note = {Number: 7 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {n/a}, pages = {792}, } @article{goncalves_neuromarketing_2023, title = {Neuromarketing and {Global} {Branding} {Reaction} {Analysis} {Based} on {Real}-{Time} {Monitoring} of {Multiple} {Consumer}'s {Biosignals} and {Emotions}}, volume = {6}, issn = {2616-4655, 2616-5163}, url = {https://rpajournals.com/jibm-2023-04-5912/}, doi = {10.37227/JIBM-2023-04-5912}, abstract = {Consumers' selections and decision-making processes are some of the most exciting and challenging topics in neuromarketing, sales, and branding. From a global perspective, multicultural influences and societal conditions are crucial to consider. Neuroscience applications in international marketing and consumer behavior is an emergent and multidisciplinary field aiming to understand consumers' thoughts, reactions, and selection processes in branding and sales. This study focuses on real-time monitoring of different physiological signals using eye-tracking, facial expressions recognition, and Galvanic Skin Response (GSR) acquisition methods to analyze consumers' responses, detect emotional arousal, measure attention or relaxation levels, analyze perception, consciousness, memory, learning, motivation, preference, and decision-making. This research aimed to monitor human subjects' reactions to these signals during an experiment designed in three phases consisting of different branding advertisements. The nonadvertisement exposition was also monitored while gathering survey responses at the end of each phase. A feature extraction module with a data analytics module was implemented to calculate statistical metrics and decision-making supporting tools based on Principal Component Analysis (PCA) and Feature Importance (FI) determination based on the Random Forest technique. The results indicate that when compared to image ads, video ads are more effective in attracting consumers' attention and creating more emotional arousal.}, language = {en}, number = {5}, urldate = {2023-05-29}, journal = {Journal of International Business and Management}, author = {Goncalves, Marcus and Lobo Marques, Joao Alexandre and Silva, Bruno Riccelli Santos and Luther, Valorie and Hayes, Sydney}, month = apr, year = {2023}, pages = {01--32}, } @article{marques_effectiveness_2023, title = {{EFFECTIVENESS} {ANALYSIS} {OF} {WATERFALL} {AND} {AGILE} {PROJECT} {MANAGEMENT} {METHODOLOGIES} – {A} {CASE} {STUDY} {FROM} {MACAU}'{S} {CONSTRUCTION} {INDUSTRY}}, volume = {12}, copyright = {Direitos autorais 2023 Revista Gestão em Análise}, issn = {2359-618X}, url = {https://periodicos.unichristus.edu.br/gestao/article/view/2508}, doi = {10.12662/2359-618xregea.v12i1.p23-38.2023}, abstract = {The adoption of project management techniques is a crucial decision for corporate governance in construction companies since the management of areas such as risk, cost, and communications is essential for the success or failure of an endeavor. Nevertheless, different frameworks based on traditional or agile methodologies are available with several approaches, which may create several ways to manage projects. The primary purpose of this work is to investigate the adequate project management methodology for the construction industry from a general perspective and consider a case study from Macau. The methodology considered semi-structured interviews and a survey comparing international and local project managers from the construction industry. The interviews indicate that most construction project managers still follow empirical methods with no specific methodology but consider the adoption of traditional waterfall approaches. In contrast, according to the survey, most project managers and construction managers agree that the project's efficacy needs to increase, namely in planning, waste minimization, communication increase, and focus on the Client's feedback. In addition, there seems to be a clear indication that agile methodology could be implemented in several types of projects, including hospitality development projects. A hybrid development approach based on the Waterfall and Agile methodologies as a tool for the project management area may provide a more suitable methodology for project managers to follow.}, language = {en}, number = {1}, urldate = {2023-03-22}, journal = {Revista Gestão em Análise}, author = {Marques, Joao Alexandre Lobo and Morais, João José Bragança dos Reis and Alves, José and Gonçalves, Marcus}, month = feb, year = {2023}, note = {Number: 1}, keywords = {PMBOK, agile, construction industry, project management methodologies}, pages = {23--38}, } @article{ribeiro_covid-19_2023, title = {{COVID}-19 {Detection} by {Means} of {ECG}, {Voice}, and {X}-ray {Computerized} {Systems}: {A} {Review}}, volume = {10}, copyright = {http://creativecommons.org/licenses/by/3.0/}, issn = {2306-5354}, shorttitle = {{COVID}-19 {Detection} by {Means} of {ECG}, {Voice}, and {X}-ray {Computerized} {Systems}}, url = {https://www.mdpi.com/2306-5354/10/2/198}, doi = {10.3390/bioengineering10020198}, abstract = {Since the beginning of 2020, Coronavirus Disease 19 (COVID-19) has attracted the attention of the World Health Organization (WHO). This paper looks into the infection mechanism, patient symptoms, and laboratory diagnosis, followed by an extensive assessment of different technologies and computerized models (based on Electrocardiographic signals (ECG), Voice, and X-ray techniques) proposed as a diagnostic tool for the accurate detection of COVID-19. The found papers showed high accuracy rate results, ranging between 85.70\% and 100\%, and F1-Scores from 89.52\% to 100\%. With this state-of-the-art, we concluded that the models proposed for the detection of COVID-19 already have significant results, but the area still has room for improvement, given the vast symptomatology and the better comprehension of individuals’ evolution of the disease.}, language = {en}, number = {2}, urldate = {2023-03-21}, journal = {Bioengineering}, author = {Ribeiro, Pedro and Marques, João Alexandre Lobo and Rodrigues, Pedro Miguel}, month = feb, year = {2023}, note = {Number: 2 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {COVID-19, artificial intelligence, computerized diagnostic systems, image processing, signal processing}, pages = {198}, } @article{cavalcante_sudden_2023, title = {Sudden cardiac death multiparametric classification system for {Chagas} heart disease's patients based on clinical data and 24-hours {ECG} monitoring}, volume = {20}, copyright = {2023 The Author(s)}, issn = {1551-0018}, url = {http://www.aimspress.com/rticle/doi/10.3934/mbe.2023402}, doi = {10.3934/mbe.2023402}, abstract = {{\textless}abstract{\textgreater}{\textless}p{\textgreater}About 6.5 million people are infected with Chagas disease (CD) globally, and WHO estimates that \$ \> million people worldwide suffer from ChHD. Sudden cardiac death (SCD) represents one of the leading causes of death worldwide and affects approximately 65\% of ChHD patients at a rate of 24 per 1000 patient-years, much greater than the SCD rate in the general population. Its occurrence in the specific context of ChHD needs to be better exploited. This paper provides the first evidence supporting the use of machine learning (ML) methods within non-invasive tests: patients' clinical data and cardiac restitution metrics (CRM) features extracted from ECG-Holter recordings as an adjunct in the SCD risk assessment in ChHD. The feature selection (FS) flows evaluated 5 different groups of attributes formed from patients' clinical and physiological data to identify relevant attributes among 57 features reported by 315 patients at HUCFF-UFRJ. The FS flow with FS techniques (variance, ANOVA, and recursive feature elimination) and Naive Bayes (NB) model achieved the best classification performance with 90.63\% recall (sensitivity) and 80.55\% AUC. The initial feature set is reduced to a subset of 13 features (4 Classification; 1 Treatment; 1 CRM; and 7 Heart Tests). The proposed method represents an intelligent diagnostic support system that predicts the high risk of SCD in ChHD patients and highlights the clinical and CRM data that most strongly impact the final outcome.{\textless}/p{\textgreater}{\textless}/abstract{\textgreater}}, language = {en}, number = {5}, urldate = {2023-03-21}, journal = {Mathematical Biosciences and Engineering}, author = {Cavalcante, Carlos H. L. and Primo, Pedro E. O. and Sales, Carlos A. F. and Caldas, Weslley L. and Silva, João H. M. and Souza, Amauri H. and Marinho, Emmanuel S. and Pedrosa, Roberto C. and Marques, João A. L. and Santos, Hélcio S. and Madeiro, João P. V. and Cavalcante, Carlos H. L. and Primo, Pedro E. O. and Sales, Carlos A. F. and Caldas, Weslley L. and Silva, João H. M. and Souza, Amauri H. and Marinho, Emmanuel S. and Pedrosa, Roberto C. and Marques, João A. L. and Santos, Hélcio S. and Madeiro, João P. V.}, year = {2023}, note = {Cc\_license\_type: cc\_by Number: mbe-20-05-402 Primary\_atype: Mathematical Biosciences and Engineering Subject\_term: Research article Subject\_term\_id: Research article}, pages = {9159--9178}, } @article{wong_exploratory_2023, title = {Exploratory {Analysis} of {Project} {Management} {Adoption} and {Maturity} {Level} of {IT} {Companies}–{A} {Comparison} between {Macao} and {Hengqin}}, volume = {11}, issn = {28109740}, url = {http://www.joams.com/show-106-594-1.html}, doi = {10.18178/joams.11.3.124-129}, number = {2}, urldate = {2024-01-14}, journal = {Journal of Advanced Management Science}, author = {Wong, Ka Seng and Lobo Marques, João Alexandre}, year = {2023}, pages = {124--129}, } @article{yan_review_2023, title = {A review on multimodal machine learning in medical diagnostics}, volume = {20}, copyright = {2023 The Author(s)}, issn = {1551-0018}, url = {http://www.aimspress.com/rticle/doi/10.3934/mbe.2023382}, doi = {10.3934/mbe.2023382}, abstract = {Nowadays, the increasing number of medical diagnostic data and clinical data provide more complementary references for doctors to make diagnosis to patients. For example, with medical data, such as electrocardiography (ECG), machine learning algorithms can be used to identify and diagnose heart disease to reduce the workload of doctors. However, ECG data is always exposed to various kinds of noise and interference in reality, and medical diagnostics only based on one-dimensional ECG data is not trustable enough. By extracting new features from other types of medical data, we can implement enhanced recognition methods, called multimodal learning. Multimodal learning helps models to process data from a range of different sources, eliminate the requirement for training each single learning modality, and improve the robustness of models with the diversity of data. Growing number of articles in recent years have been devoted to investigating how to extract data from different sources and build accurate multimodal machine learning models, or deep learning models for medical diagnostics. This paper reviews and summarizes several recent papers that dealing with multimodal machine learning in disease detection, and identify topics for future research.}, language = {en}, number = {5}, urldate = {2023-03-21}, journal = {Mathematical Biosciences and Engineering}, author = {Yan, Keyue and Li, Tengyue and Marques, João Alexandre Lobo and Gao, Juntao and Fong, Simon James and Yan, Keyue and Li, Tengyue and Marques, João Alexandre Lobo and Gao, Juntao and Fong, Simon James}, year = {2023}, note = {Cc\_license\_type: cc\_by Number: mbe-20-05-382 Primary\_atype: Mathematical Biosciences and Engineering Subject\_term: Review Subject\_term\_id: Review}, pages = {8708--8726}, } @article{khatoon_quality_2022, title = {Quality of life during the pandemic: a cross sectional study about attitude, individual perspective and behavior change affecting general population in daily life}, shorttitle = {Quality of life during the pandemic}, url = {https://digital-library.theiet.org/content/conferences/10.1049/icp.2023.0596}, doi = {10.1049/icp.2023.0596}, abstract = {Quality of life in general population before and during pandemic is topic need to be address by researcher in terms of mobility, self-care, usual activities, pain/discomfort and anxiety/depression. The study was carried out among Saudi population. Data were collected from general population using questionnaire during the period from 22 August 2021 to 10th January 2022. As a result, total 214 participants have included in this study. Among them prevalent age group include 40 years (n= 63, 29.4\%) shadowed by the age group 25-35 (n= 61, 28.5\%) while above 60 years group were least frequent (n= 1, 0.5\%). On questioning the applicants whether they were satisfied with their health and how would they rate their quality of life, their answers were as follows: yes, or satisfied (n= 86, 40.2\%), very Satisfied (n= 102, 47.7\%) Dissatisfied (n= 11, 5.1\%) and neither satisfied nor dissatisfied (n= 15, 7\%). Due to pandemic, they were rate quality of life very good (n= 94, 43.9\%), good (n= 63, 29.4 \%) poor (n= 5, 2.3 \%) and neither good and nor poor (n= 52, 24.3 \%). During pandemic 96 participants feel no change in their weight but 110 participants respond that there is increase in coffee intake during the pandemic. Similarly increased in smoking habits and decrease rate in social activities (n=119,41.4\%). The psychosomatic well-being of people has been interrupted by disturbing their social activities during pandemic.}, language = {en}, urldate = {2023-10-10}, author = {Khatoon, F. and Kumar, M. and Khalid, A. A. and Alshammari, A. D. and Khan, F. and Alshammari, R. D. and Balouch, Z. and Verma, D. and Mishra, P. and Abotaleb, M. and Makarovskikh, T. and El-kenawy, E. M. and Dutta, P. K. and Marques, J. A.}, month = jan, year = {2022}, note = {Publisher: IET Digital Library}, pages = {379--383}, } @article{marques_iot-based_2021, title = {{IoT}-{Based} {Smart} {Health} {System} for {Ambulatory} {Maternal} and {Fetal} {Monitoring}}, volume = {8}, issn = {2327-4662}, doi = {10.1109/JIOT.2020.3037759}, abstract = {The adoption of IoT for smart health applications is a relevant tool for distributed and intelligent automatic diagnostic systems. This work proposes the development of an integrated solution to monitor maternal and fetal signals for high-risk pregnancies based on IoT sensors, feature extraction based on data analytics, and an intelligent diagnostic aid system based on a 1-D convolutional neural network (CNN) classifier. The fetal heart rate and a group of maternal clinical indicators, such as the uterine tonus activity, blood pressure, heart rate, temperature, and oxygen saturation are monitored. Multiple data sources generate a significant amount of data in different formats and rates. An emergency diagnostic subsystem is proposed based on a fog computing layer and the best accuracy was 92.59\% for both maternal and fetal emergency. A smart health analytics system is proposed for multiple feature extraction and the calculation of linear and nonlinear measures. Finally, a classification technique is proposed as a prediction system for maternal, fetal, and simultaneous health status classification, considering six possible outputs. Different classifiers are evaluated and a proposed CNN presented the best results, with the F1-score ranging from 0.74 to 0.91. The results are validated based on the diagnosis provided by two specialists. The results show that the proposed system is a viable solution for maternal and fetal ambulatory monitoring based on IoT.}, number = {23}, journal = {IEEE Internet of Things Journal}, author = {Marques, João Alexandre Lobo and Han, Tao and Wu, Wanqing and Madeiro, João Paulo do Vale and Neto, Aloísio Vieira Lira and Gravina, Raffaele and Fortino, Giancarlo and de Albuquerque, Victor Hugo C.}, month = dec, year = {2021}, note = {9 citations (Crossref) [2022-09-21] Conference Name: IEEE Internet of Things Journal}, keywords = {Artificial intelligence (AI), Biomedical monitoring, Cloud computing, Feature extraction, Fetal heart rate, Internet of Things, Medical diagnostic imaging, Monitoring, convolutional neural networks (CNNs), feature extraction, fetal monitoring, health analytics, maternal monitoring}, pages = {16814--16824}, } @article{silva_neto_towards_2021, title = {Towards an efficient prognostic model for fetal state assessment}, volume = {185}, issn = {0263-2241}, url = {https://www.sciencedirect.com/science/article/pii/S0263224121009568}, doi = {10.1016/j.measurement.2021.110034}, abstract = {Monitoring signals such as fetal heart rate (FHR) are important indicators of fetal well-being. Computer-assisted analysis of FHR patterns has been successfully used as a decision support tool. However, the absence of a gold standard for the building blocks decision-making in the systems design process impairs the development of new solutions. Here we propose a prognostic model based on advanced signal processing techniques and machine learning algorithms for the fetal state assessment within a comprehensive evaluation process. Feature-engineering-based and time-series-based machine learning classifiers were modeled into three data segmentation schemas for CTU-UHB, HUFA, and DB-TRIUM datasets and the generalization performance was assessed by a two-way cross-dataset evaluation. It has been shown that the feature-based algorithms outperformed the time-series ones on data-limited scenarios. The Support Vector Machines (SVM) obtained the best results on the datasets individually: specificity (85.6\% ) and sensitivity (67.5\%). On the other hand, the most effective generalization results were achieved by the Multi-layer perceptron (MLP) with a specificity of 71.6\% and sensitivity of 61.7\%. The overall process provided a combination of techniques and methods that increased the final prognostic model performance, achieving relevant results and requiring a smaller amount of data when compared to the state-of-the-art fetal status assessment solutions.}, language = {en}, urldate = {2022-09-21}, journal = {Measurement}, author = {Silva Neto, Manuel Gonçalves da and Madeiro, João Paulo do Vale and Marques, João Alexandre Lobo and Gomes, Danielo G.}, month = nov, year = {2021}, note = {1 citations (Crossref) [2022-09-21]}, keywords = {Cardiotocography, Classification, Fetal state assessment, Prognostic model, System design}, pages = {110034}, } @article{nguyen_van_identification_2021, title = {Identification of {Latent} {Risk} {Clinical} {Attributes} for {Children} {Born} {Under} {IUGR} {Condition} {Using} {Machine} {Learning} {Techniques}}, volume = {200}, issn = {0169-2607}, url = {https://www.sciencedirect.com/science/article/pii/S0169260720316758}, doi = {10.1016/j.cmpb.2020.105842}, abstract = {Background and objective Intrauterine Growth Restriction (IUGR) is a condition in which a fetus does not grow to the expected weight during pregnancy. There are several well documented causes in the literature for this issue, such as maternal disorder, and genetic influences. Nevertheless, besides the risk during pregnancy and labour periods, in a long term perspective, the impact of IUGR condition during the child development is an area of research itself. The main objective of this work is to propose a machine learning solution to identify the most significant features of importance based on physiological, clinical or socioeconomic factors correlated with previous IUGR condition after 10 years of birth. Methods In this work, 41 IUGR (18 male) and 34 Non-IUGR (22 male) children were followed up 9 years after the birth, in average (9.1786 ± 0.6784 years old). A group of machine learning algorithms is proposed to classify children previously identified as born under IUGR condition based on 24-hours monitoring of ECG (Holter) and blood pressure (ABPM), and other clinical and socioeconomic attributes. In additional, an algorithm of relevance determination based on the classifier is also proposed, to determine the level of importance of the considered features. Results The proposed classification solution achieved accuracy up to 94.73\%, and better performance than seven state-of-the-art machine learning algorithms. Also, relevant latent factors related to HRV and BP monitoring are proposed, such as: day-time heart rate (day-time HR), day-night systolic blood pressure (day-night SBP), 24-hour standard deviation (SD) of SBP, dropped, morning cortisol creatinine, 24-hour mean of SDs of all NN intervals for each 5 minutes segment (24-hour SDNNi), among others. Conclusion With outstanding accuracy of our proposed solutions, the classification system and the indication of relevant attributes may support medical teams on the clinical monitoring of IUGR children during their childhood development.}, language = {en}, urldate = {2022-09-21}, journal = {Computer Methods and Programs in Biomedicine}, author = {Nguyen Van, Sau and Lobo Marques, J. A. and Biala, T. A. and Li, Ye}, month = mar, year = {2021}, note = {2 citations (Crossref) [2022-09-21]}, keywords = {ABPM (Ambulatory Blood Pressure Monitoring), HRV (Heart Rate Variability), IUGR (Intrauterine Growth Restriction), Machine Learning}, pages = {105842}, } @article{arraut_probability_2021, title = {The {Probability} {Flow} in the {Stock} {Market} and {Spontaneous} {Symmetry} {Breaking} in {Quantum} {Finance}}, volume = {9}, copyright = {http://creativecommons.org/licenses/by/3.0/}, issn = {2227-7390}, url = {https://www.mdpi.com/2227-7390/9/21/2777}, doi = {10.3390/math9212777}, abstract = {The spontaneous symmetry breaking phenomena applied to Quantum Finance considers that the martingale state in the stock market corresponds to a ground (vacuum) state if we express the financial equations in the Hamiltonian form. The original analysis for this phenomena completely ignores the kinetic terms in the neighborhood of the minimal of the potential terms. This is correct in most of the cases. However, when we deal with the martingale condition, it comes out that the kinetic terms can also behave as potential terms and then reproduce a shift on the effective location of the vacuum (martingale). In this paper, we analyze the effective symmetry breaking patterns and the connected vacuum degeneracy for these special circumstances. Within the same scenario, we analyze the connection between the flow of information and the multiplicity of martingale states, providing in this way powerful tools for analyzing the dynamic of the stock markets.}, language = {en}, number = {21}, urldate = {2023-04-11}, journal = {Mathematics}, author = {Arraut, Ivan and Lobo Marques, João Alexandre and Gomes, Sergio}, month = jan, year = {2021}, note = {Number: 21 Publisher: Multidisciplinary Digital Publishing Institute}, keywords = {Hermiticity, conservation of the information, degenerate vacuum, flow of information, martingale condition, random fluctuations, spontaneous symmetry breaking, vacuum condition}, pages = {2777}, } @article{silva_modelling_2021, title = {Modelling the barriers that are preventing e-commerce to thrive – a case study from {Portugal}, international journal of business excellence}, issn = {1756-0047}, abstract = {The identification of barriers for e-commerce to thrive in specific countries is a topic of great interest. This work proposes two models to study the barriers to B2C e-commerce adoption in Portugal, highlighting obstacles less exploited by previous research: the impact of offline shopping pleasure and the influence of the distance to shopping malls on online shopping intent. An online survey was conducted based on different constructs. A multivariate OLS hierarchical regression was used to analyse the proposed models regarding the intention to buy online and the number of online purchases. The results revealed that customer satisfaction is a strong predictor of intent to buy online and that perceived product risk remains a barrier to e-commerce. Consumers living in high urbanised areas have more propensity to buy online. Helpful information is provided regarding the impact of context, culture, product, and individual barriers, showing that multichannel strategies are best suited for success.}, journal = {International Journal of Business Excellence}, author = {Silva, Susana Costa e and Machado, Joana Costa and Martins, Carla and Duarte, Paulo and Marques, João Alexandre Lobo}, year = {2021}, keywords = {E-commerce barriers, Online shopping, Portugal, Retail}, } @article{li_health_2020, title = {Health and {Well}-{Being} {Education}: {Extending} the {SCARF} {Learning} {Analytics} {Model} for {Identifying} the {Learner} {Happiness} {Indicators}}, volume = {2}, copyright = {Access limited to members}, issn = {2577-4794}, shorttitle = {Health and {Well}-{Being} {Education}}, url = {https://www.igi-global.com/article/health-and-well-being-education/www.igi-global.com/article/health-and-well-being-education/260728}, doi = {10.4018/IJEACH.2020070105}, abstract = {The use of learning analytics (LA) in real-world educational applications is growing very fast as academic institutions realize the positive potential that is possible if LA is integrated in decision making. Education in schools on public health need to evolve in response to the new knowledge and th...}, language = {en}, number = {2}, urldate = {2022-09-21}, journal = {International Journal of Extreme Automation and Connectivity in Healthcare (IJEACH)}, author = {Li, Tengyue and Marques, Joao Alexandre Lobo and Fong, Simon}, month = jul, year = {2020}, note = {0 citations (Crossref) [2022-09-21] Publisher: IGI Global}, pages = {42--53}, } @article{luo_crowdsensing-based_2020, title = {Crowdsensing-{Based} {Gamification} for {Collective} {Assistance} for {Post}-{Era} of {Coronavirus} {Epidemic} in {Community} {Living}}, volume = {2}, copyright = {Access limited to members}, issn = {2577-4794}, url = {https://www.igi-global.com/article/crowdsensing-based-gamification-for-collective-assistance-for-post-era-of-coronavirus-epidemic-in-community-living/www.igi-global.com/article/crowdsensing-based-gamification-for-collective-assistance-for-post-era-of-coronavirus-epidemic-in-community-living/260729}, doi = {10.4018/IJEACH.2020070106}, abstract = {Crowdsensing exploits the sensing abilities offered by smart phones and users' mobility. Users can mutually help each other as a community with the aid of crowdsensing. The potential of crowdsensing has yet to be fully realized for improving public health. A protocol based on gamification to encoura...}, language = {en}, number = {2}, urldate = {2022-09-21}, journal = {International Journal of Extreme Automation and Connectivity in Healthcare (IJEACH)}, author = {Luo, Renfei and Marques, João Alexandre Lôbo and Ong, Kok-Leong and Fong, Simon}, month = jul, year = {2020}, note = {0 citations (Crossref) [2022-09-21] Publisher: IGI Global}, pages = {54--64}, } @article{do_vale_madeiro_evaluation_2020, title = {Evaluation of mathematical models for {QRS} feature extraction and {QRS} morphology classification in {ECG} signals}, volume = {156}, issn = {0263-2241}, url = {https://www.sciencedirect.com/science/article/pii/S0263224120301172}, doi = {10.1016/j.measurement.2020.107580}, abstract = {It is plausible to assume that the component waves in ECG signals constitute a unique human characteristic because morphology and amplitudes of recorded beats are governed by multiple individual factors. According to the best of our knowledge, the issue of automatically classifying different ’identities’ of QRS morphology has not been explored within the literature. This work proposes five alternative mathematical models for representing different QRS morphologies providing the extraction of a set of features related to QRS shape. The technique incorporates mechanisms of combining the mathematical functions Gaussian, Mexican-Hat and Rayleigh probability density function and also a mechanism for clipping the waveform of those functions. The searching for the optimal parameters which minimize the normalized RMS error between each mathematical model and a given QRS search window enables to find an optimal model. Such modeling behaves as a robust alternative for delineating heartbeats, classifying beat morphologies, detecting subtle and anomalous changes, compression of QRS complex windows among others. The validation process evaluates the ability of each model to represent different QRS morphology classes within 159 full ECG signal records from QT database and 584 QRS search windows from MIT-BIH Arrhythmia database. From the experimental results, we rank the winning rates for which each mathematical model best models and also discriminates the most predominant QRS morphologies Rs, rS, RS, qR, qRs, R, rR’s and QS. Furthermore, the average time errors computed for QRS onset and offset locations when using the corresponding winner mathematical models for delineation purposes were, respectively, 12.87±8.5 ms and 1.47±10.06 ms.}, language = {en}, urldate = {2022-09-21}, journal = {Measurement}, author = {do Vale Madeiro, João Paulo and Lobo Marques, João Alexandre and Han, Tao and Coury Pedrosa, Roberto}, month = may, year = {2020}, note = {13 citations (Crossref) [2022-09-21]}, keywords = {ECG feature extraction, Mathematical modeling, Morphology classification, QRS complex delineation}, pages = {107580}, } @article{marques_importance_2020, title = {The {Importance} of {Readiness} for {Change}, a {Leadership} {Perspective} {Based} on a {Case} {Study} in {Macau}, {SAR} {China}}, doi = {10.18178/joams.8.4.116-120}, journal = {Journal of Advanced Management Science}, author = {Marques, João and Reis, Joana and Phillips, Jenny O. L. and Diakite, Ansoumane}, month = jan, year = {2020}, note = {0 citations (Crossref) [2022-09-21]}, pages = {116--120}, } @article{arraut_probability_2020, title = {On the probability flow in the {Stock} market {I}: {The} {Black}-{Scholes} case}, volume = {1}, copyright = {© 2019. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.}, shorttitle = {On the probability flow in the {Stock} market {I}}, url = {https://search.proquest.com/docview/2332255379?pq-origsite=primo}, abstract = {It is known that the probability is not a conserved quantity in the stock market, given the fact that it corresponds to an open system. In this paper we analyze the flow of probability in this system by expressing the ideal Black-Scholes equation in the Hamiltonian form. We then analyze how the non-conservation of probability affects the stability of the prices of the Stocks. Finally, we find the conditions under which the probability might be conserved in the market, challenging in this way the non-Hermitian nature of the Black-Scholes Hamiltonian.}, language = {English}, urldate = {2021-02-03}, journal = {arXiv.org}, author = {Arraut, Ivan and Au, Alan and Tse, Alan Ching-biu and Marques, Joao Alexandre Lobo}, year = {2020}, note = {Place: Ithaca, United States Publisher: Cornell University Library, arXiv.org Section: Quantitative Finance University: Cornell University Library arXiv.org}, keywords = {General Finance}, pages = {1--10}, } @article{lan_multi-view_2020, title = {Multi-view convolutional neural network with leader and long-tail particle swarm optimizer for enhancing heart disease and breast cancer detection}, url = {10.1007/s00521-020-04769-y}, doi = {10.1007/s00521-020-04769-y}, urldate = {2021-02-03}, journal = {Neural Computing and Applications}, author = {Lan, K. and Liu, L. and Li, T. and Chen, Y. and Fong, S. and Marques, J.A.L. and Wong, R.K. and Tang, R.}, year = {2020}, note = {8 citations (Crossref) [2022-09-21]}, } @article{marques_nonlinear_2020, title = {Nonlinear characterization and complexity analysis of cardiotocographic examinations using entropy measures}, volume = {76}, url = {10.1007/s11227-018-2570-8}, doi = {10.1007/s11227-018-2570-8}, number = {2}, urldate = {2021-02-03}, journal = {Journal of Supercomputing}, author = {Marques, J.A.L. and Cortez, P.C. and Madeiro, J.P.V. and Albuquerque, V.H.C. and Fong, S.J. and Schlindwein, F.S.}, year = {2020}, note = {17 citations (Crossref) [2022-09-21]}, pages = {1305--1320}, } @article{armando_carlos_hombo_nogueira_influencia_2019, title = {Influência da nova estrutura fiscal de impostos de {Angola} na gestão de escolas privadas do municipio do {Lobito}}, url = {http://doi.org/10.12662/2359-618xregea.v8i2.p11-30.2019}, doi = {10.12662/2359-618xregea.v8i2.p11-30.2019}, urldate = {2021-02-03}, journal = {Revista Gestao em Analise}, author = {{Armando Carlos Hombo Nogueira} and {Luis Miguel Pacheco} and {Marcus Antonio Almeida Rodrigues}}, month = jun, year = {2019}, note = {0 citations (Crossref) [2022-09-21]}, } @article{de_aguiar_lead_2019, title = {Lead: {An} {iOS} {Application} to {Help} in the {Construction} of {New} {Habits}}, volume = {9}, shorttitle = {Lead}, url = {http://www.ijiee.org/index.php?m=content&c=index&a=show&catid=87&id=820}, number = {4}, journal = {International Journal of Information and Electronics Engineering}, author = {de Aguiar, André Wescley Oliveira and Bezerra, Jagni Dasa Horta and Marques, João Alexandre Lobo and de Alexandria, Auzuir Ripardo}, year = {2019}, } @article{do_vale_madeiro_evaluating_2019, title = {Evaluating {Mathematical} {Models} for {Morphological} {Classification} of the {QRS} {Complex}}, volume = {2019-September}, url = {10.23919/CinC49843.2019.9005790}, doi = {10.23919/CinC49843.2019.9005790}, urldate = {2021-02-03}, journal = {Computing in Cardiology}, author = {Do Vale Madeiro, J.P. and Barreto, D. and Marques, J.A.L. and Salinet, J.L.}, year = {2019}, } @article{marques_automatic_2019, title = {Automatic {Cardiotocography} {Diagnostic} {System} {Based} on {Hilbert} {Transform} and {Adaptive} {Threshold} {Technique}}, volume = {7}, issn = {2169-3536}, url = {https://ieeexplore.ieee.org/abstract/document/8682138}, doi = {10.1109/ACCESS.2018.2877933}, abstract = {The visual analysis of cardiotocographic examinations is a very subjective process. The accurate detection and segmentation of the fetal heart rate (FHR) features and their correlation with the uterine contractions in time allow a better diagnostic and the possibility of anticipation of many problems related to fetal distress. This paper presents a computerized diagnostic aid system based on digital signal processing techniques to detect and segment changes in the FHR and the uterine tone signals automatically. After a pre-processing phase, the FHR baseline detection is calculated. An auxiliary signal called detection line is proposed to support the detection and segmentation processes. Then, the Hilbert transform is used with an adaptive threshold for identifying fiducial points on the fetal and maternal signals. For an antepartum (before labor) database, the positive predictivity value (PPV) is 96.80\% for the FHR decelerations, and 96.18\% for the FHR accelerations. For an intrapartum (during labor) database, the PPV found was 91.31\% for the uterine contractions, 94.01\% for the FHR decelerations, and 100\% for the FHR accelerations. For the whole set of exams, PPV and SE were both 100\% for the identification of FHR DIP II and prolonged decelerations.}, journal = {IEEE Access}, author = {Marques, J. A. Lobo and Cortez, P. C. and Madeiro, J. P. D. V. and Fong, S. J. and Schlindwein, F. S. and Albuquerque, V. H. C. D.}, year = {2019}, note = {13 citations (Crossref) [2022-09-21] Conference Name: IEEE Access}, keywords = {Acceleration, Biomedical monitoring, Cardiography, Cardiotocography (CTG), Databases, FHR DIP II, FHR accelerations, FHR baseline detection, FHR decelerations, Fetal heart rate, Hilbert transform, Hilbert transforms, Monitoring, PPV, Transforms, accurate fetal heart rate feature detection, accurate fetal heart rate feature segmentation, adaptive threshold technique, antepartum database, automatic cardiotocography diagnostic system, auxiliary signal, cardiotocographic examinations, computerized diagnostic aid system, digital signal processing techniques, fetal distress, fetal heart rate (FHR), fetal signals, maternal signals, medical signal detection, medical signal processing, obstetrics, patient monitoring, positive predictivity value, preprocessing phase, segmentation processes, uterine contractions, uterine contractions (UC), uterine tone signals, visual analysis}, pages = {73085--73094}, } @article{lan_multi-view_2018, title = {Multi-view {Convolution} {Neural} {Network} with {Swarm} {Search} {Based} {Hyperparameter} {Optimization} for {Enhancing} {Heart} {Disease} and {Breast} {Cancer} {Detection}}, url = {10.1109/ISCMI.2018.8703249}, doi = {10.1109/ISCMI.2018.8703249}, urldate = {2021-02-03}, journal = {5th International Conference on Soft Computing and Machine Intelligence, ISCMI 2018}, author = {Lan, K. and Li, T. and Fong, S. and Marques, J.A.L. and Wong, R.K.}, year = {2018}, note = {2 citations (Crossref) [2022-09-21]}, pages = {140--146}, } @article{paulo_do_vale_madeiro_heart_2015, title = {A {Heart} {Rate} {Variability}-based {Smart} {Approach} to {Analyze} {Frailty} in {Older} {Adults}}, issn = {22344624}, url = {http://smartcr.org/view/download.php?filename=smartcr_vol5no4p002.pdf}, doi = {10.6029/smartcr.2015.04.002}, abstract = {This paper presents an algorithm that applies metrics derived from automatic QRS detection and segmentation in electrocardiogram signals for analyzing Heart Rate Variability to study the evolution of metrics in the frequency domain of a clinical procedure. The analysis was performed on three sets of elderly people, who are categorized according to frailty phenotype. The first set was comprised of frail elderly, the second pre-frail elderly, and the third robust elderly. Investigators from many disciplines have been encouraged to contribute to the understanding of molecular and physiological changes in multiple systems that may increase the vulnerability of frail elderly. In this work, the frailty phenotype can be characterized by unintentional weight loss, as self-reported, fatigue assessed by self-report, grip strength (measured directly), physical activity level assessed by self-report and gait speed (measured). The results obtained demonstrate the existence of significant differences between Heart Rate Variability metrics for the three groups, especially considering a higher preponderance for sympathetic nervous system for the group of robust patients in response to postural maneuver.}, urldate = {2023-03-22}, journal = {The Smart Computing Review}, author = {Paulo do Vale Madeiro, João and César Cortez, Arnaldo Aires Peixoto Júnior, Paulo and Alexandre Lôbo Marques, João and Alisson Pessoa Guimarães, Antônio and Hebert da Silva Felix, John}, month = aug, year = {2015}, } @article{gutierrez-adrianzen_pathophysiological_2015, title = {Pathophysiological, cardiovascular and neuroendocrine changes in hypertensive patients during the hemodialysis session}, volume = {29}, copyright = {2015 Macmillan Publishers Limited}, issn = {1476-5527}, url = {https://www.nature.com/articles/jhh201493}, doi = {10.1038/jhh.2014.93}, abstract = {The pathophysiological mechanisms of arterial hypertension during hemodialysis (HD) in patients with end-stage renal disease (ESRD) are still poorly understood. The aim of this study is to investigate physiological, cardiovascular and neuroendocrine changes in patients with ESRD and its correlation with changes in blood pressure (BP) during the HD session. The present study included 21 patients with ESRD undergoing chronic HD treatment. Group A (study) consisted of patients who had BP increase and group B (control) consisted of those who had BP reduction during HD session. Echocardiograms were performed during the HD session to evaluate cardiac output (CO) and systemic vascular resistance (SVR). Before and after the HD session, blood samples were collected to measure brain natriuretic peptide (BNP), catecholamines, endothelin-1 (ET-1), nitric oxide (NO), electrolytes, hematocrit, albumin and nitrogen substances. The mean age of the studied patients was 43±4.9 years, and 54.6\% were males. SVR significantly increased in group A (P{\textless}0.001). There were no differences in the values of BNP, NO, adrenalin, dopamin and noradrenalin, before and after dialysis, between the two groups. The mean value of ET-1, post HD, was 25.9 pg ml−1 in group A and 13.3 pg ml−1 in group B (P={\textless}0.001). Patients with ESRD showed different hemodynamic patterns during the HD session, with significant BP increase in group A, caused by an increase in SVR possibly due to endothelial dysfunction, evidenced by an increase in serum ET-1 levels.}, language = {en}, number = {6}, urldate = {2023-10-18}, journal = {Journal of Human Hypertension}, author = {Gutiérrez-Adrianzén, O. A. and Moraes, M. E. A. and Almeida, A. P. and Lima, J. W. O. and Marinho, M. F. and Marques, A. L. and Madeiro, J. P. V. and Nepomuceno, L. and da Silva Jr, J. M. S. and Silva Jr, G. B. and Daher, E. F. and Rodrigues Sobrinho, C. R. M.}, month = jun, year = {2015}, note = {Number: 6 Publisher: Nature Publishing Group}, keywords = {End-stage renal disease, Haemodialysis, Hypertension}, pages = {366--372}, }