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

Advances in mechanistic modeling, machine learning, and biomedical data integration are making it possible to move beyond “one-size-fits-all” evidence and ...

In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of drug discovery.

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 ...

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

Read more about AI-driven learning analytics struggle to deliver measurable gains in higher education on Devdiscourse ...

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

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