AI model using head CT imaging predicts in-hospital mortality for patients with gunshot wounds to the head with high discriminative performance.

Please provide your email address to receive an email when new articles are posted on . Researchers found 54% of studies had risk for bias due to inadequate population selection. Moreover, 30% of ...

ROC curves illustrating the discriminative ability of the VR-specific 30-day mortality prediction models. (A–C) Performance of the high VR model in the ARDSnet training cohort (A), internal validation ...

Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may underestimate risk in elderly East Asian patients. Researchers from Japan used ...

Predictive models are elusive but highly sought after in medicine. They help clinicians and patients make more informed decisions about the diagnostic and therapeutic strategies that one should take ...

No current models accurately predict time to death in patients with kidney failure. New mortality prediction models should be developed for patients with end-stage kidney disease (ESKD), as current ...

† For urbanization, AAMR 1999-2020. *P-value <0.05. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not include a full text component.

It would be greatly beneficial to physicians trying to save lives in intensive care units if they could be alerted when a patient's condition rapidly deteriorates or shows vitals in highly abnormal ...

This study applied three models—random forest (RF), gradient boosting regression (GBR), and linear regression (LR)—to predict county-level LC mortality rates across the United States. Model ...

This study validates the Predicting Risk of CVD Events (PREVENT) score across diverse racial and ethnic populations, highlighting its effectiveness in predicting cardiovascular risk and mortality, ...