A machine learning lung cancer risk prediction model outperformed logistic regression, supporting improved risk assessment and more efficient radiology based lung cancer screening.

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Using machine learning models, researchers at Michigan Medicine have identified a potential way to diagnose amyotrophic lateral sclerosis, or ALS, earlier from a blood sample, a study suggests.

ABSTRACT: Heart disease remains one of the leading causes of mortality worldwide, accounting for millions of deaths annually. Early detection of individuals at risk is essential for reducing ...

1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...

In May 2025, the U.S. Army’s Soldier Lethality Project at the Picatinny Arsenal in New Jersey announced the official type classification of SIG Sauer’s M7 rifle and M250 automatic rifle, previously ...

Introduction: Stroke remains one of the leading causes of global mortality and long-term disability, driving the urgent need for accurate and early risk prediction tools. Traditional models such as ...

1 Department Health informatics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia 2 Department of Community Health Nursing, School of Nursing ...

Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...