Machine learning could help predict how people with depression respond to treatment

Researchers at Trinity College Dublin have found that a machine learning model could help clinicians predict which people with depression are more likely to improve with digital cognitive behavioral ...
ahajournals.org

Translating Mechanistic Insights Into Action and Revealing New Pathways: Machine Learning Approaches in Heart Failure With Preserved Ejection Fraction

Heart failure with preserved ejection fraction is a prevalent condition that carries a high morbidity and mortality, with limited treatment options. Obtaining and integrating critical mechanistic ...
Frontiers

Clinical decision system for renal cell carcinoma integrating interpretable machine learning algorithms

Kidney cancer is a highly heterogeneous oncologic disease with historically poor prognosis. Precise assessment of the risk of distal metastasis can facilitate risk stratification and improve prognosis ...
Scientific Research Publishing

Comparative Study of Machine Learning Techniques for Early Detection of Heart Diseases ()

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for millions of deaths each year according to the World Health Organization (WHO). Early detection of these diseases ...
ahajournals.org

Using Machine Learning to Risk Stratify Emergency Department Patients With Chest Pain but No Acute Myocardial Infarction: A Multicenter Retrospective Analysis

This study aimed to develop a machine learning‐based model to predict the risk of major adverse cardiac events (MACE) in patients presenting to the emergency department (ED) with chest pain, for whom ...
IEEE

Early heart disease prediction using machine learning Algorithms

Abstract: Heart disease ranks among the most perilous ailments of our time, taking a toll on thousands of lives a year. Detection in its early stages can be lifesaver. Machine learning is a subset of ...
Scientific Research Publishing

Azam, Z., Islam, M.M. and Huda, M.N. (2023) Comparative Analysis of Intrusion Detection Systems and Machine Learning-Based Model Analysis through Decision Tree. IEEE Access, 11 ...

ABSTRACT: Blasting is considered an indispensable process in mining excavation operations. Generally, only a small percentage of the total energy of blasting is consumed in the fragmentation and ...
IEEE

Heart Disease Detection Using Different Machine Learning Algorithms

Abstract: Now a days, Heart Disease had became an significant issue world wide. Initial prediction of heart disease can be done using Machine learning(ML). The Primary objective of writing this paper ...
BMJ

Parsimonious machine learning model to predict 1-year mortality and procedural futility after transcatheter aortic valve replacement

Background Current risk scores inadequately predict long-term mortality after transcatheter aortic valve replacement (TAVR), limiting their ability to guide decisions around procedural futility. We ...