Prospective Evaluation of a Machine-Learning Prediction Model for Missed Radiology Appointments.

The term "no-show" refers to scheduled appointments that a patient misses, or for which she arrives too late to utilize medical resources. Accurately predicting no-shows creates opportunities to intervene, ensuring that patients receive needed medical resources. A machine-learning (ML) model can accurately identify individuals at high no-show risk, to facilitate strategic and targeted interventions.

Assessment of Machine Learning vs Standard Prediction Rules for Predicting Hospital Readmissions.

Importance: Hospital readmissions are associated with patient harm and expense. Ways to prevent hospital readmissions have focused on identifying patients at greatest risk using prediction scores.

Objective: To identify the type of score that best predicts hospital readmissions.