首页|University of Toronto Reports Findings in Oral Cancer (Length of Stay Prediction Models for Oral Cancer Surgery: Machine Learning, Statistical and ACS-NSQIP)
University of Toronto Reports Findings in Oral Cancer (Length of Stay Prediction Models for Oral Cancer Surgery: Machine Learning, Statistical and ACS-NSQIP)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Oncology - Oral Cancer is the subject of a report. According to news reporting from Toronto, Canada, b y NewsRx journalists, research stated, “Accurate prediction of hospital length o f stay (LOS) following surgical management of oral cavity cancer (OCC) may be as sociated with improved patient counseling, hospital resource utilization and cos t. The objective of this study was to compare the performance of statistical mod els, a machine learning (ML) model, and The American College of Surgeons Nationa l Surgical Quality Improvement Program’s (ACS-NSQIP) calculator in predicting LO S following surgery for OCC.”
TorontoCanadaNorth and Central Ameri caCancerCyborgsEmerging TechnologiesHealth and MedicineHospitalsMach ine LearningMouth NeoplasmsOncologyOral CancerSurgery
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