The brain’s sweet spot: How criticality could unlock learning, memory—and prevent Alzheimer’s Date: June 25, 2025 Source: Washington University in St. Louis Summary: Our brains may work best ...

Alzheimer's Disease Detection using ResNet-18 and Grad-CAM This project uses a deep learning model (ResNet-18) to classify MRI brain scans and detect Alzheimer's disease. Grad-CAM is applied to ...

This study explores deep learning techniques that can help diagnose eye conditions, focusing on diabetic retinopathy (DR). By using cutting-edge technology in image processing and artificial ...

This study developed and validated a deep learning algorithm for detecting MCI in CAD populations using retinal images. The robustness of the algorithm was enhanced by integrating models of four ...

Tech & Science Precision in the preclinical phase: Mahesh Recharla proposes deep learning models for early MS and Alzheimer’s detection A leading expert in AI-driven healthcare innovation ...

Alzheimer’s disease is a neurological disorder. Research on early detection and classification using machine learning techniques has become essential in recent years. This paper focuses on developing ...

Using the APTOS 2019 Blindness Detection dataset, which includes diverse, labeled retinal images, we train, test, and benchmark deep learning models under standardized conditions, employing Python and ...

Keywords: Alzheimer patients multimodal data, retinal vessel segmentation, biomarker extraction, preliminary patients screening, deep learning Citation: Jiang H, Qian Y, Zhang L, Jiang T and Tai Y ...

Using high-resolution retinal images, a novel AI model detects Alzheimer’s disease and mild cognitive impairment early, offering hope for more timely, noninvasive, and affordable dementia care.