The potential benefits and pitfalls of this rapidly evolving technology for dermatologists are debated at AAD 2026.

A biology-guided artificial intelligence model applied to routine pathology slides accurately predicted outcomes and response ...

Somewhere, a 17-year-old has built an artificial intelligence tool designed to identify malaria and other blood diseases from ...

A computational method called scSurv, developed by researchers at Institute of Science Tokyo, links individual cells to patient outcomes using widely available bulk RNA sequencing data. The approach ...

WASHINGTON, March 4 (Reuters) - U.S. President Donald Trump is using a preventative ‌treatment for a red rash on his neck, according to his physician, but the White House declined on Wednesday to ...

The saliva circulating in your mouth contains troves of microbial information about the rest of your body and is easier to collect than blood samples. Today, a few drops of spit can help detect ...

Abstract: The Early Skin Disease Prediction system which it utilizes the methods and technique of deep learning, for example it is using ResNet-50 convolutional neural networks along with the ...

A full-stack medical analysis application that detects 23 different types of skin diseases using Deep Learning. This project consists of a React.js Frontend for the user interface and a Python Flask ...

MediScan is an AI-powered project that predicts **skin diseases** from images using a deep learning model. It provides a modern web interface (Next.js) where users can upload an image and receive a ...

Baseline biomarker analysis and clinical outcomes of the PD-1/TGFβR2 bispecific antibody INCA33890 in patients with non-MSI-H metastatic colorectal cancer (mCRC). This is an ASCO Meeting Abstract from ...