Predict+ uses machine learning to predict patient outcomes after shoulder replacement, according to a news release. It aims to help surgeons personalize treatment modalities for patients.
“By inputting data points like a patient’s age, surgical history, diagnosis, pain level and pre-operative range of motion, the Predict+ machine learning algorithms can predict the shoulder replacement outcomes for my patients based on thousands of other patients who have already had surgery,” Dr. Shah said in the release.
At the Becker’s 32nd Annual Meeting: The Business and Operations of ASCs, taking place October 29-31 in Chicago, ASC leaders, surgeons and healthcare executives will explore strategies to drive growth, enhance operational performance, navigate reimbursement challenges and prepare for the future of ambulatory surgery. Apply for complimentary registration now.
