From brain scans to alloys: Teaching AI to make sense of complex research data
UNIVERSITY PARK, Pa. — Artificial intelligence (AI) is increasingly used to analyze medical images, materials data and scientific measurements, but many systems struggle when real-world data do not match ideal conditions. Measurements collected from different instruments, experiments or simulations often vary widely in resolution, noise and reliability. Traditional machine-learning models typically assume those differences are negligible — an assumption that can limit accuracy and trustworthiness.
To address this issue, Penn State researchers have developed a new artificial intelligence framework with potential implications for fields ranging from Alzheimer’s disease ...