Machine Learning methods applied to audit of surgical margins after curative surgery for Head and Neck Cancer

Most surgical specialities have attempted to address the concern of unfair comparison of outcomes by ‘risk-adjusting’ data in order to benchmark speciality specific outcomes indicative of quality of care. We explore the ability to predict for positive margin status in order that effective benchmarking that accounts for complexity of case-mix is possible.
Source: The British Journal of Oral and Maxillofacial Surgery - Category: ENT & OMF Authors: Source Type: research