Condition: Artificial Intelligence (AI) · Machine Learning · Joint Replacement · Sponsor: Istituto Ortopedico Rizzoli
The goal of this observational study is to develop and pre-validate a machine learning algorithm to predict early recovery of mobility in patients undergoing hip or knee joint replacement surgery. The primary research question is: Can a machine learning model accurately classify patients with faster versus slower recovery of autonomous mobility in the first days after joint replacement surgery? Patients who have undergone elective hip or knee arthroplasty and received post-operative physiotherapy will have their clinical and perioperative data collected retrospectively (2020-2023) and prospectively (March 2026-December 2027). The algorithm will be trained on retrospective data and tested prospectively to evaluate its predictive performance for early mobilization and length of hospital stay.
This description comes directly from the study's public registry record.
Mattia Morri · +390516366694 · mattia.morri@ior.it
Always discuss trial participation with your own doctor first.
| SAITeR IRCCS Istituto Ortopedico Rizzoli | Bologna, Italy | Recruiting |
| Azienda U.S.L. - IRCCS di Reggio Emilia | Reggio Emilia, Italy | Not Yet Recruiting |
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Source record: clinicaltrials.gov/study/NCT07333560