A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...
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.
Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...
Researchers in the Nanoscience Center at the University of Jyväskylä, Finland, have developed a pioneering computational ...