This predictive model built on readily acquired clinical data provides encouraging results for the detection of residual disease. External validation and prospective studies implementing the model in ...

New research reveals a model to predict chronic immune thrombocytopenia in children at diagnosis. Learn how it could guide ...

An artificial intelligence (AI) model developed by researchers at The University of Texas MD Anderson Cancer Center ...

A machine learning model can accurately predict an individual’s risk of developing hepatocellular carcinoma (HCC) using routine clinical data, according to a new study. The findings point to a ...

PLSKB: An Interactive Knowledge Base to Support Diagnosis, Treatment, and Screening of Lynch Syndrome on the Basis of Precision Oncology We used an innovative machine learning approach to analyze ...

Machine learning algorithms utilizing electronic health records can effectively predict two-year dementia risk among American Indian/Alaska Native adults aged 65 years and older, according to a ...

Final random-forest-based models outperformed all publicly available risk scores on internal and external test sets.

Mount Sinai researchers have created an analytic tool using machine learning that can predict cardiovascular disease risk in patients with obstructive sleep apnea ...

The severity of symptoms in posttraumatic stress disorder (PTSD) varies greatly across individuals in the first year after trauma and it remains difficult to predict whether someone might worsen, ...

A team of researchers has successfully predicted abnormal grain growth in simulated polycrystalline materials for the first time -- a development that could lead to the creation of stronger, more ...