Revolutionizing healthcare: the role of artificial intelligence in clinical practice
Introduction Healthcare systems are complex and challenging for all stakeholders, but
artificial intelligence (AI) has transformed various fields, including healthcare, with the …
artificial intelligence (AI) has transformed various fields, including healthcare, with the …
The role of artificial intelligence in fighting the COVID-19 pandemic
The first few months of 2020 have profoundly changed the way we live our lives and carry
out our daily activities. Although the widespread use of futuristic robotaxis and self-driving …
out our daily activities. Although the widespread use of futuristic robotaxis and self-driving …
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 …
pandemic and has expanded all over the world. Because of increasing number of cases day …
An enhanced ResNet-50 deep learning model for arrhythmia detection using electrocardiogram biomedical indicators
R Anand, SV Lakshmi, D Pandey, BK Pandey - Evolving Systems, 2024 - Springer
Electrocardiogram (ECG) is one among the most common detecting techniques in the
analysis and detection of cardiac arrhythmia adopted due to its cost efficiency and simplicity …
analysis and detection of cardiac arrhythmia adopted due to its cost efficiency and simplicity …
Adaptive extreme edge computing for wearable devices
Wearable devices are a fast-growing technology with impact on personal healthcare for both
society and economy. Due to the widespread of sensors in pervasive and distributed …
society and economy. Due to the widespread of sensors in pervasive and distributed …
Explainable prediction of acute myocardial infarction using machine learning and shapley values
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 …
imperative for the timely provision of medical intervention and the reduction of its mortality …
Exploration of physiological sensors, features, and machine learning models for pain intensity estimation
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 …
This subjective pain assessment results in suboptimal treatment plans, over-prescription of …
One-dimensional CNN approach for ECG arrhythmia analysis in fog-cloud environments
Cardiovascular diseases are considered the number one cause of death across the globe
which can be primarily identified by the abnormal heart rhythms of the patients. By …
which can be primarily identified by the abnormal heart rhythms of the patients. By …
Machine learning and artificial intelligence in the service of medicine: Necessity or potentiality?
T Alsuliman, D Humaidan, L Sliman - Current research in translational …, 2020 - Elsevier
Motivation As a result of the worldwide health care system digitalization trend, the produced
healthcare data is estimated to reach as much as 2314 Exabytes of new data generated in …
healthcare data is estimated to reach as much as 2314 Exabytes of new data generated in …
Heartbeats classification using hybrid time-frequency analysis and transfer learning based on ResNet
Y Zhang, J Li, S Wei, F Zhou, D Li - IEEE Journal of Biomedical …, 2021 - ieeexplore.ieee.org
The classification of heartbeats is an important method for cardiac arrhythmia analysis. This
study proposes a novel heartbeat classification method using hybrid time-frequency analysis …
study proposes a novel heartbeat classification method using hybrid time-frequency analysis …