Frontiers

Develop a diagnostic tool for dementia using machine learning and non-imaging features

Background: Early identification of Alzheimer’s disease or mild cognitive impairment can help guide direct prevention and supportive treatments, improve outcomes, and reduce medical costs. Existing ...
Frontiers

Modeling Plasmodium falciparum Diagnostic Test Sensitivity Using Machine Learning With Histidine-Rich Protein 2 Variants

Malaria, predominantly caused by Plasmodium falciparum, poses one of largest and most durable health threats in the world. Previously, simplistic regression-based models have been created to ...
GitHub

Stroke-Identification-A-Machine-Learning-Based-Diagnostic-Model-Using-Neuroimages

Brain Health Classification This repository contains code for a machine learning project that classifies brain images into "normal" and "stroke" categories using a Support Vector Machine (SVM) ...
health.economictimes.indiatimes

IIT Kharagpur's 'Covirap' diagnostic machine gets ICMR certification

NEW DELHI: 'COVIRAP,' the diagnostic machine developed by the Indian Institute of Technology (IIT) Kharagpur researchers, has been successfully validated for its efficacy in Covid-19 detection by the ...
rmdopen.bmj

Identification of a machine learning-based diagnostic model for axial spondyloarthritis in rheumatological routine care using a random forest approach

Objectives In axial spondyloarthritis (axSpA), early diagnosis is crucial, but diagnostic delay remains long and diagnostic criteria do not exist. We aimed to identify a diagnostic model that ...
The Irish Times

Diagnostic machine for heart disease

A NEW diagnostic machine for congenital heart disease will allow cardiologists at the Mater hospital in Dublin to make a diagnosis… A NEW diagnostic machine for congenital heart disease will allow ...