The Lancet

When to and when not to use machine learning in risk prediction models

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...
ascopubs.org

Predictive modeling by tumor type: Comparing performance and feature importance of machine learning–based predictive models in patients with hematologic and solid tumors.

Benchmarking clinical reasoning and accuracy of large language models on breast oncology multiple-choice questions.
insideHPC

Interview: Feature Stores for Machine Learning

Lately, there has been a lot of discussion in the machine learning space about the concept of feature stores. Feature stores were first developed by the Uber Michelangelo team to support the ...
Open Heart

Bridging machine learning and clinical practice: a multicentre nomogram for 90-day graft failure risk stratification in heart transplantation

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...