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.

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 ...

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; ...

Applying artificial intelligence techniques to cardiac ultrasound data may make it easier to identify patients with advanced heart failure, a new study has found. The study—led by investigators at ...

Subtilitas, A Precision Translational Medicine Platform Subtilitas integrates non-invasive skin sampling, advanced molecular profiling, and artificial intelligence/machine learning analysis to enable ...

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 ...

A multi-institutional research team has demonstrated how artificial intelligence and machine learning can optimize therapy selection and dosing for septic shock, a life-threatening complication that ...

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

There are more candidates on the waitlist for a liver transplant than there are available organs, yet about half the time a match is found with a donor who dies after cardiac arrest following ...

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 ...

A new study led by York University found that not only could machine-learning models accurately pinpoint differences in healthy controls and those living with HIV, but also found outliers in both ...