machine learning

Grand Challenges at the Interface of Engineering and Medicine
Grand Challenges at the Interface of Engineering and Medicine 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)
Over the past two decades Biomedical Engineering has emerged as a major discipline that bridges societal needs of human health care with the development of novel technologies. Every medical institution… read more

Optimized Clinical Feature Analysis for Improved Cardiovascular Disease Risk Screening
Optimized Clinical Feature Analysis for Improved Cardiovascular Disease Risk Screening 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)
Objective: To develop a clinical decision support tool that can predict cardiovascular disease (CVD) risk with high accuracy while requiring minimal clinical feature input, thus reducing the time and effort… read more

Infra-Red Imaging to Detect Respirator Leak in Healthcare Workers During Fit-Testing Clinic
Infra-Red Imaging to Detect Respirator Leak in Healthcare Workers During Fit-Testing Clinic 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)
Objective: This study addressed the problem of objectively detecting leaks in P2 respirators at point of use, an essential component for healthcare workers’ protection. To achieve this, we explored the… read more

A Framework for Efficient N-Way Interaction Testing in Case/Control Studies With Categorical Data
Author(s)3: Aristos Aristodimou, Athos Antoniades, Efthimios Dardiotis, Eleni M. Loizidou, George M. Spyrou, Christina Votsi, Kyproula Christodoulou, Marios Pantzaris, Nikolaos Grigoriadis, Georgios M. Hadjigeorgiou, Theodoros Kyriakides, Constantinos S. Pattichis
A Framework for Efficient N-Way Interaction Testing in Case/Control Studies With Categorical Data 150 150 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)

Most common diseases are influenced by multiple gene interactions and interactions with the environment. Performing an exhaustive search to identify such interactions is computationally expensive and needs to address the…

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Accelerometry-Based Digital Gait Characteristics for Classification of Parkinson’s Disease: What Counts?
Author(s)3: Silvia Del Din, Cameron Kirk, Lynn Rochester, Christopher Buckley, Maria Encarna Mico-Amigo, Claudia Mazza, Michael Dunne-Willows, Jian Quing Shi, Rana Zia Ur Rehman, Lisa Alcock
Accelerometry-Based Digital Gait Characteristics for Classification of Parkinson’s Disease: What Counts? 800 545 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)

Gait may be a useful biomarker that can be objectively measured with wearable technology to classify Parkinson’s disease (PD). This study aims to: (i) comprehensively quantify a battery of commonly…

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Predicting Lymphoma Development by Exploiting Genetic Variants and Clinical Findings in a Machine Learning-Based Methodology With Ensemble Classifiers in a Cohort of Sjögren’s Syndrome Patients
Author(s)3: Clio Mavragani, Konstantina D. Kourou, Costas Papaloukas, Michalis Voulgarelis, Andreas Goules, Dimitrios I. Fotiadis, Themis Exarchos, Andrianos Nezos, Eleni I. Georga, Vasileios C. Pezoulas, Athanasios G. Tzioufas, Haralampos M. Moutsopoulos
Predicting Lymphoma Development by Exploiting Genetic Variants and Clinical Findings in a Machine Learning-Based Methodology With Ensemble Classifiers in a Cohort of Sjögren’s Syndrome Patients 800 534 IEEE Open Journal of Engineering in Medicine and Biology (OJEMB)

Lymphoma development constitutes one of the most serious clinico-pathological manifestations of patients with Sjögren’s Syndrome (SS). Over the last decades the risk for lymphomagenesis in SS patients has been studied…

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