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 ...

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 ...

Among hospitalized patients with cirrhosis, a machine learning (ML) model enhanced mortality prediction compared with traditional methods and was consistent across country income levels in a large ...

Patients with myelodysplastic syndromes (MDS) exhibit diverse disease trajectories necessitating different clinical approaches ranging from watch-and-wait strategies to hematopoietic stem cell ...

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 ...

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

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 ...

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 ...

Researchers developed and externally validated a machine learning model to predict the 28-day mortality risk in ICU patients with sepsis complicated by acute respiratory failure. Using routinely ...

A team of researchers from Boston-based Harvard Medical School, Boston-based Massachusetts General Hospital and IBM Research developed a risk score to predict patient outcomes after cirrhosis-related ...