Dynamic prediction of cancer-associated thrombosis to guide prophylactic anticoagulation. Age distribution of metastatic cancer patients and chemotherapy discontinuation rates.

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

The Opioid Risk Tool for Opioid Use Disorder may help identify patients with chronic noncancer pain at increased risk for OUD ...

Cardiovascular disease continues to be the leading cause of death worldwide. To save lives, constantly improving diagnostic ...

COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...

DataZapp brings AI and machine learning to deliver affordable, predictive demand generation and marketing data for home ...

The team utilized machine learning to analyze public data from the National Health and Nutrition Examination Survey.

Machine learning models accurately predict survival after surgery for upper tract urothelial cancer, supporting personalised follow up and adjuvant treatment decisions.