BOSTON--(BUSINESS WIRE)--Orthopaedic surgeon Sarav Shah, MD, is the first in the Boston area to use a predictive modeling tool called Predict+®, a patient-specific outcome predictor for shoulder replacement.
For those struggling with chronic shoulder pain caused by injury or arthritis, total shoulder replacement may be an option. This procedure involves removing diseased bone and cartilage and replacing it with orthopaedic implants.
Predict+ is a clinical decision support tool that uses machine learning to provide predictions of individual patient outcomes after shoulder replacement surgery. With it, surgeons can leverage predictive analytics and patient data from thousands of shoulder replacement patients who have already had surgery to predict a new patients’ outcome and potential level of satisfaction with the procedure.
“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,” said Dr. Shah, of New England Baptist Orthopedic Specialists.
“Predict+ allows me to guide and offer the best treatment modality for optimized outcome that is tailored to each individual patient,” Dr. Shah continued.
In the Boston area, Dr. Shah is the first to make this option available to patients. A double board certified and dual fellowship trained orthopaedic surgeon, Dr. Shah was recently named chief of the division of Sports Medicine at New England Baptist Hospital.
For more information about Predict+ or to schedule an appointment with Dr. Shah, call 617-754-6630 or visit https://www.nebh.org/find-a-doctor/doctors/sarav-shah/.
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