Fluid-reduced-solid interaction (FrSI): Physics-and projection-based model reduction for cardiovascular applications

M Hirschvogel, M Balmus, M Bonini… - Journal of Computational …, 2024 - Elsevier
Fluid-solid interaction (FSI) phenomena play an important role in many biomedical
engineering applications. While FSI techniques and models have enabled detailed …

Machine Learning-Based Heat Sink Optimization Model for Single-Phase Immersion Cooling

J Herring, P Smith… - International …, 2022 - asmedigitalcollection.asme.org
Traditional air-cooling along with corresponding heat sinks are beginning to reach
performance limits, requiring lower air-supply temperatures and higher air-supply flowrates …

Heart disease prediction with 100% accuracy, using machine learning: Performance improvement with features selection and sampling

F Sabah, Y Chen, Z Yang, A Raheem… - 2023 8th IEEE …, 2023 - ieeexplore.ieee.org
Heart diseases are commonly diagnosed by using the technique of; angiography which is
time consuming procedure. Therefore, researchers have been encouraged to find out the …

Autoantibodies to Oxidatively Modified Peptide: Potential Clinical Application in Coronary Artery Disease

IJ Tsai, WC Shen, JZ Wu, YS Chang, CY Lin - Diagnostics, 2022 - mdpi.com
Coronary artery disease (CAD) is a global health issue. Lipid peroxidation produces various
by-products that associate with CAD, such as 4-hydroxynonenal (HNE) and …

Comparative Analysis of Machine Learning Methods for Multi-Year CVD Prediction

AA Gozali - 2023 International Conference on Smart …, 2023 - ieeexplore.ieee.org
Cardiovascular diseases (CVDs) significantly contribute to global mortality, and early
detection is crucial for preventing severe complications and reducing mortality rates …

[PDF][PDF] Exploring Important Factors in Predicting Heart Disease Based on Ensemble-Extra Feature Selection Approach

H Abubaker, F Muchtar, AR Khairuddin, ANA Nuar… - Baghdad Science …, 2024 - iasj.net
Heart disease is a significant and impactful health condition that ranks as the leading cause
of death in many countries. In order to aid physicians in diagnosing cardiovascular diseases …

Applying Neural Networks to Recover Values of Monitoring Parameters for COVID-19 Patients in the ICU

S Celada-Bernal, G Pérez-Acosta… - Mathematics, 2023 - mdpi.com
From the moment a patient is admitted to the hospital, monitoring begins, and specific
information is collected. The continuous flow of parameters, including clinical and analytical …

AI based prediction for heart disease: a comparative analysis and an improved machine learning approach

J Raval, JP Verma, SNM Islam, R Jain… - 2022 6th Asian …, 2022 - ieeexplore.ieee.org
Heart disease problems are growing day by day in the world. Many factors are responsible
for increasing the chance of heart attack and any other disease. Many countries have a low …

E-DigitTool: A New-Fangled Framework for Disease Prediction and Diagnosis in Remote Healthcare Applications

R Lakshmi Priya, V Kumaraswamy, NKB Sunil… - Iranian Journal of …, 2024 - Springer
The seamless communication between people and objects made possible by the Internet of
Things (IoT) greatly improves our quality of life. It is especially important in the remote …

Big data analytics in healthcare environment using chaotic red deer optimizer with deep learning for disease classification model

RH Kumar, G Sunitha - Multimedia Tools and Applications, 2024 - Springer
Deep learning (DL) and big data analytics are powerful tools when combined for disease
detection and healthcare applications. They enable the processing of vast amounts of …