Study in a Sentence: The U.S. Food and Drug Administration approved an Investigational New Drug (IND) application using efficacy data solely from Qureator’s human vascularized organoid model, moving ...

Brain tumors represent a significant health challenge in India, with approximately 28,000 new cases diagnosed annually. Conventional deep learning approaches for MRI-based segmentation often struggle ...

Background: Despite advances in immunotherapy, durable responses in lung cancer remain limited to a subset of patients, underscoring the need for biomarkers capturing spatial immune-tumor interactions ...

Additional visualizations highlighting the comparison between the proposed two-stage AG-VQ-VAE network (without skip connections) and the single-stage AG-UNet (with skip connections) are presented.

1 Department of Mathematics and Statistics, Loyola University Chicago, Chicago, IL, USA. 2 Department of Mathematics and Computer Science, Islamic Azad University, Science and Research Branch, Tehran, ...

Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...

SAN DIEGO, July 30, 2025 /PRNewswire/ -- Cortechs.ai, a pioneer in AI-powered medical imaging solutions, is pleased to announce the immediate availability of its latest release of the FDA-cleared ...

Abstract: The purpose of this paper is to study of how machine learning algorithms, artificial intelligence, semantic segmentation and fine recognition can be used to enhance computer vision in order ...

Trained on multi-hospital data, iSeg spots moving tumors doctors sometimes miss, edging radiation treatment toward pinpoint perfection. Credit: Stock An AI system called iSeg is reshaping radiation ...

This repository is the official code for the paper "Enhanced MRI Brain Tumor Detection and Classification via Topological Data Analysis and Low-Rank Tensor Decomposition" by Serena Grazia De ...