A shortage of inpatient beds and nurses during the coronavirus disease 2019 pandemic has lent priority to safe same-day discharge after surgery. The minimally invasive nature of robotic surgery has allowed an increasing number of procedures to be don...
Journal of gastroenterology and hepatology
Feb 1, 2021
The future of gastrointestinal bleeding will include the integration of machine learning algorithms to enhance clinician risk assessment and decision making. Machine learning algorithms have shown promise in outperforming existing clinical risk score...
IMPORTANCE: Machine learning (ML) algorithms can identify patients with cancer at risk of short-term mortality to inform treatment and advance care planning. However, no ML mortality risk prediction algorithm has been prospectively validated in oncol...
The Journal of the American Academy of Orthopaedic Surgeons
Jul 1, 2020
INTRODUCTION: Patient selection for outpatient total shoulder arthroplasty (TSA) is important to optimizing patient outcomes. This study aims to develop a machine learning tool that may aid in patient selection for outpatient total should arthroplast...
BACKGROUND: Inflammatory bowel disease (IBD) is a chronic disease characterized by unpredictable episodes of flares and periods of remission. Tools that accurately predict disease course would substantially aid therapeutic decision-making. This study...
Medical decision making : an international journal of the Society for Medical Decision Making
Feb 1, 2017
OBJECTIVE: To design a precision medicine approach aimed at exploiting significant patterns in data, in order to produce venous thromboembolism (VTE) risk predictors for cancer outpatients that might be of advantage over the currently recommended mod...