Artificial intelligence for risk assessment on primary prevention of coronary artery disease

SF Chen, S Loguercio, KY Chen, SE Lee… - Current Cardiovascular …, 2023 - Springer
Abstract Purpose of Review Coronary artery disease (CAD) is a common and etiologically
complex disease worldwide. Current guidelines for primary prevention, or the prevention of …

Cardiac disease risk prediction using machine learning algorithms

AA Stonier, RK Gorantla, K Manoj - Healthcare Technology …, 2023 - Wiley Online Library
Heart attack is a life‐threatening condition which is mostly caused due to coronary disease
resulting in death in human beings. Detecting the risk of heart diseases is one of the most …

Machine learning for predicting hepatitis B or C virus infection in diabetic patients

SH Kim, SH Park, H Lee - Scientific Reports, 2023 - nature.com
Highly prevalent hepatitis B and hepatitis C virus (HBV and HCV) infections have been
reported among individuals with diabetes. Given the frequently asymptomatic nature of …

Developing a machine-learning model for real-time prediction of successful extubation in mechanically ventilated patients using time-series ventilator-derived …

KY Huang, YL Hsu, HC Chen, MH Horng… - Frontiers in …, 2023 - frontiersin.org
Background Successful weaning from mechanical ventilation is important for patients
admitted to intensive care units. However, models for predicting real-time weaning outcomes …

Identification of high-risk patients for referral through machine learning assisting the decision making to manage minor ailments in community pharmacies

N Amador-Fernández, SI Benrimoj… - Frontiers in …, 2023 - frontiersin.org
Background: Data analysis techniques such as machine learning have been used for
assisting in triage and the diagnosis of health problems. Nevertheless, it has not been used …

A hybrid approach for medical images classification and segmentation to reduce complexity

A Kumar, S Bhatia, R Bhardwaj, KU Singh… - Innovations in Systems …, 2023 - Springer
The computational domain facilitates the performance of novel and innovative medical
research and development tasks by providing support and computational power. This …

A self-predictive diagnosis system of liver failure based on multilayer neural networks

F Dashti, A Ghaffari, A Seyfollahi, B Arasteh - Multimedia Tools and …, 2024 - Springer
The lack of symptoms in the early stages of liver disease may cause wrong diagnosis of the
disease by many doctors and endanger the health of patients. Therefore, earlier and more …

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 …

Mitigating class imbalance in heart disease detection with machine learning

A Pandey, BA Shivaji, M Acharya… - Multimedia Tools and …, 2024 - Springer
Within the context of contemporary civilization, cardiovascular disease has emerged as a
severe health issue that impacts individuals of all ages and from a variety of backgrounds …