A new artificial intelligence-based method accurately sorts cancer patients into groups that have similar characteristics before treatment and similar outcomes after treatment, according to a study led by investigators at Weill Cornell Medicine.
Leveraging the power of AI and machine learning technologies, researchers at Weill Cornell Medicine developed a more effective model for predicting how patients with muscle-invasive bladder cancer will respond to chemotherapy.
A machine-learning tool created by Weill Cornell Medicine and Hospital for Special Surgery (HSS) investigators can help distinguish subtypes of rheumatoid arthritis (RA), which may help scientists find ways to improve care for the complex condition.
Researchers at Weill Cornell Medicine have used machine learning to define three subtypes of Parkinson’s disease based on the pace at which the disease progresses.
While the peak of the COVID-19 pandemic seems to have passed, the effects of post-COVID conditions on public health remain. A new study led by Weill Cornell Medicine and NewYork-Presbyterian investigators has found that the risk of long COVID and its symptoms present very differently across diverse populations and suggests that further investigation is needed to accurately define the disease and improve diagnosis and treatment.
Weill Cornell Medicine and NewYork-Presbyterian investigators have built a machine-learning tool that can predict SARS-CoV-2 infection based on age, gender, race and 27 routine laboratory test results.
