International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...
BMJ

Machine learning approaches to injury risk prediction in sport: a scoping review with evidence synthesis

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 ...
BMJ Open

Generating actionable insights to support point-of-care suicide risk decision-making in a safety-net healthcare system: a machine learning approach to predicting dynamic risk ...

Background Suicide rates have increased over the last couple of decades globally, particularly in the United States and among populations with lower economic status who present at safety-net ...
ascopubs.org

Machine-learning (ML) model predictive for chemotherapy toxicity and termination in a real-world community oncology practice.

Dynamic prediction of cancer-associated thrombosis to guide prophylactic anticoagulation. Age distribution of metastatic cancer patients and chemotherapy discontinuation rates.
Yale Environment 360

A step toward clinically useful brain-behavior machine learning models

Relating brain activity to behavior is an ongoing aim of neuroimaging research as it would help scientists understand how the brain begets behavior — and perhaps open new opportunities for ...

How Predictive Analytics Improves Decision-Making In Educational Institutions

Implementing predictive analytics can become one of the biggest competitive differentiators for any educational institution ...