Discover how AI healthcare technology and machine learning diagnosis are transforming disease detection, improving accuracy, and reshaping patient care in today's evolving medical landscape.

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a ...

As new technologies emerge and extend the capabilities of physicians, researchers and scientists, the landscape of healthcare is also bound to change. One such example is machine learning, in which a ...

A machine learning model based on electronic health record data can provide updated predictions of preeclampsia risk, ...

How people with compromised immune systems respond to vaccines is an important area of immunological research. A study led by York University has found that not only could machine-learning models ...

The AI in precision medicine market shows strong growth prospects driven by the need for personalized therapies amid rising chronic diseases. Key opportunities include advancements in AI for ...

AI and machine-learning programs have entered medicine in many ways, including, but not limited to, helping to identify outbreaks of infectious diseases that may have an impact on public health; ...

Researchers developed an AI model that analyzes health records to predict preeclampsia risk late in pregnancy, helping doctors monitor mothers and prevent complications.

Machine-learning models accurately pinpointed differences in immune responses in healthy controls and those living with HIV.

The adoption of machine learning approaches in systematic reviews is fundamentally transforming evidence-based medicine. Traditionally, systematic reviews have involved painstaking manual screening of ...

The Division of Infectious Diseases celebrates a paper published documenting antibiotic stewardship efforts here at UAB. The publication by first-author Rachael Lee, MD, with senior author Pete Pappas ...