AI advancements improve Alzheimer's detection and breast cancer research

Researchers are utilizing artificial intelligence to advance early diagnosis and cellular analysis in neurodegenerative and oncological diseases.

In Spain, investigators from the Hospital Universitario Severo Ochoa and the Universidad Carlos III de Madrid (UC3M) have developed a machine learning methodology to study nocturnal brain waves. This non-invasive tool aims to detect early neuronal alterations associated with Alzheimer's disease by analyzing electrical activity during sleep, a period when the brain clears metabolic waste like beta-amyloid protein. The study, published in GeroScience, seeks to provide a window into biological processes that occur years before clinical symptoms appear.

Separately, researchers at the University of Southampton have developed CenSegNet, a deep learning platform designed to analyze centrosome anomalies in breast cancer. By analyzing over 330,000 centrosomes across 911 tumor samples, the tool identified two distinct types of cellular alterations. While not yet a clinical diagnostic test, the platform allows for high-resolution study of how these cellular irregularities are distributed within tumors and how they relate to tumor grade and patient survival.