Comparison of deep learning approaches to predict COVID-19 infection

TB Alakus, I Turkoglu - Chaos, Solitons & Fractals, 2020 - Elsevier
The SARS-CoV2 virus, which causes COVID-19 (coronavirus disease) has become a
pandemic and has expanded all over the world. Because of increasing number of cases day …

PulDi-COVID: Chronic obstructive pulmonary (lung) diseases with COVID-19 classification using ensemble deep convolutional neural network from chest X-ray …

YH Bhosale, KS Patnaik - Biomedical Signal Processing and Control, 2023 - Elsevier
Abstract Background and Objective In the current COVID-19 outbreak, efficient testing of
COVID-19 individuals has proven vital to limiting and arresting the disease's accelerated …

Technological advancements and elucidation gadgets for Healthcare applications: An exhaustive methodological review-part-I (AI, big data, block chain, open-source …

S Siripurapu, NK Darimireddy, A Chehri, B Sridhar… - Electronics, 2023 - mdpi.com
In the realm of the emergence and spread of infectious diseases with pandemic potential
throughout the history, plenty of pandemics (and epidemics), from the plague to AIDS (1981) …

Big-ECG: Cardiographic predictive cyber-physical system for stroke management

I Hussain, SJ Park - IEEE Access, 2021 - ieeexplore.ieee.org
Electrocardiogram (ECG) is sensitive to autonomic dysfunction and cardiac complications
derived from ischemic or hemorrhage stroke and is supposed to be a potential prognostic …

Explainable prediction of acute myocardial infarction using machine learning and shapley values

L Ibrahim, M Mesinovic, KW Yang, MA Eid - Ieee Access, 2020 - ieeexplore.ieee.org
The early and accurate detection of the onset of acute myocardial infarction (AMI) is
imperative for the timely provision of medical intervention and the reduction of its mortality …

Computer modeling of the heart for ECG interpretation—a review

O Dössel, G Luongo, C Nagel, A Loewe - Hearts, 2021 - mdpi.com
Computer modeling of the electrophysiology of the heart has undergone significant
progress. A healthy heart can be modeled starting from the ion channels via the spread of a …

Exploration of physiological sensors, features, and machine learning models for pain intensity estimation

F Pouromran, S Radhakrishnan, S Kamarthi - Plos one, 2021 - journals.plos.org
In current clinical settings, typically pain is measured by a patient's self-reported information.
This subjective pain assessment results in suboptimal treatment plans, over-prescription of …

An ECG generative model of myocardial infarction

W Que, C Han, X Zhao, L Shi - Computer Methods and Programs in …, 2022 - Elsevier
Abstract Background and Objective Computer-aided diagnosis (CAD) of Myocardial
Infarction (MI) using machine learning depends on a large amount of clinical …

In silico study of the mechanisms of hypoxia and contractile dysfunction during ischemia and reperfusion of hiPSC cardiomyocytes

M Forouzandehmehr, M Paci… - Disease Models & …, 2024 - journals.biologists.com
Interconnected mechanisms of ischemia and reperfusion (IR) has increased the interest in
IR in vitro experiments using human induced pluripotent stem cell-derived cardiomyocytes …

Cancer classification using machine learning and HRV analysis: preliminary evidence from a pilot study

M Vigier, B Vigier, E Andritsch, AR Schwerdtfeger - Scientific Reports, 2021 - nature.com
Most cancer patients exhibit autonomic dysfunction with attenuated heart rate variability
(HRV) levels compared to healthy controls. This research aimed to create and evaluate a …