Home Specialties Specialties Browse Articles Posters Abstracts Cureus Collections Specialties Allergy / Immunology Anatomy Anesthesiology Cardiac / Thoracic / Vascular Surgery Cardiology Dentistry Dermatology Emergency Medicine Endocrinology / Diabetes / Metabolism Environmental Health Epidemiology / Public Health Family / General Practice Forensic Medicine Gastroenterology General Surgery Genetics Geriatrics Healthcare Technology Health Policy Hematology HIV /

Home Specialties Specialties Browse Articles Posters Abstracts Cureus Collections Specialties Allergy / Immunology Anatomy Anesthesiology Cardiac / Thoracic / Vascular Surgery Cardiology Dentistry Dermatology Emergency Medicine Endocrinology / Diabetes / Metabolism Environmental Health Epidemiology / Public Health Family / General Practice Forensic Medicine Gastroenterology General Surgery Genetics Geriatrics Healthcare Technology Health Policy Hematology HIV /

Viewpoint Corresponding Author: Ma'n H Zawati, PhD Centre of Genomics and Policy McGill University 740 Dr Penfield Avenue, #5210 Montreal, QC, H3A 0G1 Canada Phone: 1 (514) 398 4806 Email: Abstract Technology is increasingly being used in decision-making in all fields, particularly in health care. Automated decision-making promises to change medical practice and potentially

Abstract We thoroughly investigated the generalizability of deep learning models trained on electroencephalography (EEG) data to detect Alzheimer's disease and dementia at the individual subject level. Although average model performance appears strong, it may obscure large inter-individual variability, raising concerns for clinical deployment. We trained a Hopfield-enhanced deep neural network on a publicly available EEG

Summary of the Flexynesis data integration and analysis workflow. Credit: Nature Communications (2025). DOI: 10.1038/s41467-025-63688-5 Nearly 50 new cancer therapies are approved every year. This is good news. "But for patients and their treating physicians, it is becoming increasingly difficult to keep track and to select the treatment methods from which the people affected—each with

Scientists taking on two of the world’s most pressing health challenges are now making speedy progress with help from AI in finding drug targets, predicting disease risk, and designing tailored treatments. Diabetes and cancer are rising health concerns globally, with increasing numbers of people affected. AI can help combat both diseases. Photo by Towfiqu barbhuiya

Introduction Remote sensing image classification is a fundamental step in understanding and interpreting Earth observation data, underpinning numerous applications from land-use analysis to environmental monitoring [1]. Over the years, researchers have developed a variety of approaches to classify high-resolution aerial and satellite imagery. Early methods relied heavily on hand-crafted features and traditional classifiers, for example

Overview of study design (created with biorender.com). Credit: Alzheimer's & Dementia (2025). DOI: 10.1002/alz.14601 A new study led by researchers from the Yong Loo Lin School of Medicine at the National University of Singapore (NUS Medicine) has demonstrated that artificial intelligence (AI) analysis of retinal photographs can predict an individual's risk of cognitive decline and