The efficient management of hospital resources, particularly in terms of bed utilisation and staff allocation, is increasingly critical in modern healthcare systems. Predictive modelling for hospital ...

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

Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...

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 ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

ACE developed a data gathering and analysis proof of concept for more accurate air drops that lays the groundwork for predictive modelling. Impact: A ...

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 ...

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 ...