University of Florida lab predicts patient cancer treatment outcomes through artificial intelligence
Dr. Raquel Dias discusses her lab’s use of artificial intelligence to predict patient treatment outcomes across life sciences, agricultural sciences, and human health.
9don MSN
AI tools improve diagnostics and patient outcome prediction in resource-limited health care settings
After a cardiac arrest, families and doctors are often faced with agonizing uncertainty about a patient's chances of recovery ...
Social vulnerability is linked to adverse obstetric outcomes, the authors say, with more socially vulnerable individuals experiencing higher rates of negative pregnancy outcomes. In a recent study, ...
The incidence of severe maternal morbidity remains high among patients with sickle cell disease, but a novel risk calculator ...
n this study, 773 untreated breast cancer patients from all over China were collected and followed up for at least 5 years. We obtained clinical data from 773 cases, RNA sequencing data from 752 cases ...
The FecMap model trained in an iterative manner. An FL communication is completed by (1) training the local model, (2) uploading to the server, (3) computing the global model, and (4) updating the ...
NEW ORLEANS, LA—A risk model based on data from the Society of Thoracic Surgeons (STS) Adult Cardiac Surgery Database (ACSD) ...
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 ...
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