Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...

In spontaneous intracerebral hemorrhage patients, features of hematoma expansion can be visualized and predicted from non-contrast computed tomography using transport-based morphometry.

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

Researchers developed and validated a machine-learning algorithm for predicting nutritional risk in patients with nasopharyngeal carcinoma.

Nigeria faces enormous public service challenges from traffic congestion in high urbanised areas to insecurity, healthcare delays, and inconsistent public planning. But with the right use of ...

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 ...

Bioprocess modeling is undergoing a transformative phase with the advent of digital technologies like artificial intelligence (AI) and machine learning ...

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models ...