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 ...
AHA/ASA Journals

Criteria to Assess the Predictive and Clinical Utility of Novel Models, Biomarkers, and Tools for Risk of Cardiovascular Disease: A Scientific Statement From the American Heart ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...
AHA/ASA Journals

Second- and Third-Generation BCR-ABL Tyrosine Kinase Inhibitors and the Risk of Pulmonary Arterial Hypertension: A Prevalent New-User Design

BACKGROUND: BCR-ABL tyrosine kinase inhibitors (TKIs) have been increasingly linked to pulmonary arterial hypertension (PAH) since 2009, although supporting evidence is limited. Our objective was to ...
North Penn Now

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...