Machine learning has emerged as a transformative approach in the design and evaluation of steel alloys, offering data-driven models that complement traditional physics-based methods. By training ...

Predictive analytics is a powerful tool that uses data to forecast future outcomes and trends. It leverages historical data, statistical modelling techniques and machine learning algorithms to ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

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.

Modern credit risk management now leans significantly on predictive modelling, moving far beyond traditional approaches. As lending practices grow increasingly intricate, companies that adopt advanced ...

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

The climate economics index stress-tests reveal that climate change will impact 48 nations, encompassing 90% of the global economy, and evaluate their overall climate resilience Machine learning (ML) ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

Developing a new drug can take years of research and cost millions of dollars. Still, more than 90% of drug candidates fail in clinical trials, with even more that never make it to the clinical stage.

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 ...