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 ...
News Medical

Combining machine learning with statistical methods can provide accurate models for disease risk prediction

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...
EurekAlert!

Integrating machine learning with statistical methods enhances disease risk prediction models

Scientists from Peking University conducts a systematic review of studies on integrating machine learning into statistical methods in disease prediction models. Researchers from Peking University have ...
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 ...

AI model more accurately predicts cardiac event risk from PET scan data

Cardiovascular disease continues to be the leading cause of death worldwide. To save lives, constantly improving diagnostic ...