Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

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

Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...

Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more ...

Artificial intelligence tools are increasingly being developed to predict cancer biology directly from microscope images, ...

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications after stem cell and bone marrow transplants, according to new research ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

BIOPREVENT’ AI tool predicts transplant-related immune conflict and mortality risk using biomarkers, helping doctors ...

Research from the University of Warwick suggests that many AI systems may be using visual shortcuts rather than true biology, ...

The DNA foundation model Evo 2 has been published in the journal Nature. Trained on the DNA of over 100,000 species across ...

Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average diagnosis time?