Litcius/Paper detail

Machine Learning Predicts the Fall Risk of Total Hip Arthroplasty Patients Based on Wearable Sensor Instrumented Performance Tests

J Polus, Riley A. Bloomfield, Edward M. Vasarhelyi, Brent A. Lanting, Matthew G. Teeter

2020The Journal of Arthroplasty26 citationsDOI

Topics & Concepts

Receiver operating characteristicWearable computerMachine learningLinear discriminant analysisArtificial intelligenceSupport vector machineClassifier (UML)Cross-validationMedicineComputer scienceEmbedded systemTotal Knee Arthroplasty OutcomesBalance, Gait, and Falls PreventionProsthetics and Rehabilitation Robotics
Machine Learning Predicts the Fall Risk of Total Hip Arthroplasty Patients Based on Wearable Sensor Instrumented Performance Tests | Litcius