Among patients with chronic noncancer pain, a novel machine learning model effectively predicts opioid use disorder risk.

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

In-hospital outcomes of acute pulmonary embolism in patients with gastrointestinal cancer: A nationwide study. This is an ASCO Meeting Abstract from the 2024 ASCO Gastrointestinal Cancers Symposium.

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

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 ...

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 ...

Keysight Technologies has introduced a new Machine Learning Toolkit as part of its latest Device Modelling Software Suite, aiming to reduce the time required for semiconductor device modelling and ...