IEEE

Breast Cancer Classification using Machine Learning Techniques with Explainable AI

Abstract: All the symptoms have been analyzed using several machine learning algorithms for diagnosing breast cancer. This paper utilizes the Breast Cancer Wisconsin (Diagnostic) data set to show how ...
BMJ Open

Development and evaluation of a diagnostic aiding tool for differentiating tropical fevers using artificial intelligence approach: a study protocol from tertiary care hospital ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...
Scientific Research Publishing

Early Alzheimer’s Disease Detection from Short Speech Samples Using Lightweight, Interpretable Linguistic Markers ()

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...
Oncology Nurse Advisor

Machine Learning Model Predicts Nutritional Risk in Nasopharyngeal Carcinoma

Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.
Hosted on MSN

Tree grows through machine, Heavy D tests if it will start

A machine with a tree growing through it is tested for operation. Opinion: James Talarico might be the antidote to MAGA Christianity Ford CEO Jim Farley said Trump would halve the EV market by ending ...
IEEE

Prediction of Multidimensional Poverty Status With Machine Learning Classification at Household Level: Empirical Evidence From Tanzania

Abstract: Over fifty percent of the population in Tanzania suffers from multidimensional poverty. Because of the high poverty rate and slow improvement, ending poverty by the year 2030 remains ...