Predictive Analytics: Key Models and Practical Applications

Discover how predictive analytics uses data-driven models like decision trees and neural networks to forecast outcomes and ...
BMJ

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...
The American Journal of Managed Care

Novel Machine Learning Model Improves MASLD Detection in Type 2 Diabetes

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...
Forbes

The Vital Difference Between Machine Learning And Generative AI

Artificial intelligence (AI) is transforming our world, but within this broad domain, two distinct technologies often confuse people: machine learning (ML) and generative AI. While both are ...
ascopubs.org

Machine learning–based classification of cancer types using genomic profiling data from the Australian Molecular Screening and Therapeutics (MoST) program.

Early detection of lung cancer in smokers using miRNA profiles and a hybrid deep learning framework. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...
Purdue University

AI and Machine Learning

The AI and Machine Learning major is one of two specialized majors in Purdue University’s 100% online Master of Science in Artificial Intelligence program. This major equips you with advanced ...
The Council of Europe

Common ethical challenges in AI

The impact of AI systems cannot always be attributed to epistemic or ethical failures. Much of their impact can appear initially ethically neutral in the absence of obvious harm. A separate set of ...