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; ...

Priya Hays, Hays Documentation Specialists, LLC, discusses biomarker discovery through artificial intelligence and ...

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

Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average ...

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

"Both studies emphasize our unique approach to using machine learning and big data in academic medicine," said Jason Moore, Ph.D., professor and chair of the Department of Computational Biomedicine at ...

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 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 ...

BIOPREVENT’ AI tool predicts transplant-related immune conflict and mortality risk using biomarkers, helping doctors ...

Melkani's study, “Automated assessment of cardiac dynamics in aging and dilated cardiomyopathy Drosophila models using machine learning,” was published in Communications Biology (A Nature Portfolio ...

CHARTwatch, a machine learning model, shows promise in reducing patient mortality and improving outcomes in hospital settings, according to new CMAJ study. Study: Clinical evaluation of a machine ...