Detecting knee osteoarthritis and its discriminating parameters using random forests

• Published in: Medical engineering & physics Vol. 43; pp. 19 - 29
• Main Authors: Kotti, Margarita, Duffell, Lynsey D., Faisal, Aldo A., McGregor, Alison H.
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.05.2017; Butterworth-Heinemann
• Subjects: Case-Control Studies; Diagnosis, Computer-Assisted - methods; Ground reaction forces; Humans; Knee osteoarthritis; Machine Learning; Osteoarthritis, Knee - diagnosis; Radiology; Random forests; Ground reaction forces; Knee osteoarthritis; Osteoarthritis; Random forests; Machine learning; OA; GRFs

• An algorithmic method that detects knee osteoarthritis.• Machine learning, specifically random forests, is applied on ground reaction forces.• Discriminating parameters of knee osteoarthritis are automatically detected.• Parameters have a clinical interpretation and are in line with medical litera...