R. Shah

Data for registry and quality review can be retrospectively collected using natural language processing from unstructured charts of arthroplasty patients.

T. Vail, S. Bini, R. Shah, 2020, The bone & joint journal.

Machine Learning Algorithms Can Use Wearable Sensor Data to Accurately Predict Six-Week Patient-Reported Outcome Scores Following Joint Replacement in a Prospective Trial.

S. Bini, M. Zaid, Ilya Bendich, 2019, The Journal of arthroplasty.

Variation in the Thickness of Knee Cartilage. The Use of a Novel Machine Learning Algorithm for Cartilage Segmentation of Magnetic Resonance Images.

S. Majumdar, V. Pedoia, T. Vail, 2019, The Journal of arthroplasty.

Incremental inputs improve the automated detection of implant loosening using machine-learning algorithms.

Valentina Pedoia, Romil F Shah, Stefano A Bini, 2020, The bone & joint journal.

Optimal Sampling Frequency for Wearable Sensor Data in Arthroplasty Outcomes Research. A Prospective Observational Cohort Trial.

S. Bini, M. Zaid, Ilya Bendich, 2019, The Journal of arthroplasty.