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 ...

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, ...

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 ...

Artificial intelligence (AI) and machine learning (ML) systems have become central to modern data-driven decision-making. They are now widely applied in fields as diverse as healthcare, finance, ...

Infinite dilution activity coefficient is a key thermodynamic parameter in solvent design for chemical processes. Although ...

A new study published in JCO Clinical Cancer Informatics demonstrates that machine learning models incorporating patient-reported outcomes and wearable sensor data can predict which patients with ...

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 ...