Managing complex medical conditions often requires the simultaneous use of multiple different drugs, referred to as polypharmacy. While necessary, this significantly increases the risk of drug-drug ...

With wildfires growing more destructive both in the United States and around the world, University at Buffalo researchers have conducted one of the most extensive evaluations to date of artificial ...

Researchers have built an artificial intelligence model that identifies acromegaly, a dangerous growth hormone disorder, by analyzing photographs of the back of the hand and a clenched fist. The model ...

In organelle imaging, segmentation aims to accurately delineate pixels or voxels corresponding to target organelles from background, noise, and other cellular structures in microscopy images, thereby ...

Indore: In a breakthrough that could improve early cancer detection and make screening more accessible, researchers at ...

A research team co-led by scientists at the Netherlands Cancer Institute (NKI) and Oncode Institute has developed a deep learning model, PARM (promoter activity regulatory model) that offers up new ...

We study the stability and convergence of training deep ResNets with gradient descent. Specifically, we show that the parametric branch in the residual block should be scaled down by a factor $\tau =O ...

This project implements a conditional Generative Adversarial Network (cGAN) for automatic grayscale image colorization, inspired by Pix2Pix. The goal is to predict chrominance (ab channels in Lab ...

Gates, who turned 70 on October 28, has previously denied any connections to Epstein's vile sex trafficking ring and confessed he "foolish to spend any time with him" at all. The tech billionaire said ...

This project uses computer vision to predict PSA (Professional Sports Authenticator) grades (1-10) for collectible cards by analyzing both front and back images. The model achieves 0.76 Quadratic ...

Deep learning models have become indispensable in medical image analysis, particularly for detecting and classifying ocular diseases. Automated diagnostic systems are promising to improve accuracy and ...