A new study published in the Journal of Neurology1 detailed the development of 2 machine learning–based tools that were able ...

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

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 ...

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 ...

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 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 ...

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 ...

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 ...

Using Python, web scraping, and advanced algorithms, the solution aggregates real-time data from marketplaces to deliver ...

In my latest Signal Spot, I had my Villanova students explore machine learning techniques to see if we could accurately ...