Discover how AI is transforming nutritional science by turning complex diet and omics data into predictive tools that reshape chronic disease prevention and personalized care.

The partnership integrates high-resolution multi-omics data generation with predictive multimodal machine learning to support biopharma decision-making in neurology.

Sensor data from wearable devices analyzed over five years reveals walking and posture differences that predict fall risk in Parkinson’s patients. Study: Predicting future fallers in Parkinson’s ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

A Stanford-led study published in Nature on Feb. 26 found that age-related changes witnessed in diseases like Alzheimer’s may be related to a relatively untapped area of research in the brain. The ...

FIU Researchers are training AI to detect heart conditions, like aortic stenosis and heart failure, by analyzing heart sound data to improve early diagnosis and risk prediction. The future of heart ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

Cancer, Alzheimer’s, and other diseases follow a pathway in the human body. It starts at the molecular and cellular levels, and through a series of complex interactions can lead to the development and ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.