Predicting serious postoperative complications and evaluating racial fairness in machine learning algorithms for metabolic and bariatric surgery-Reference-Cited by-同舟云学术

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Predicting serious postoperative complications and evaluating racial fairness in machine learning algorithms for metabolic and bariatric surgery

Published:2024-08 Issue: Volume: Page:
ISSN:1550-7289
Container-title:Surgery for Obesity and Related Diseases
language:en
Short-container-title:Surgery for Obesity and Related Diseases

Author:

Kang Dong-Won,Zhou Shouhao,Torres Russell,Chowdhury Abhinandan^ORCID,Niranjan Suman^ORCID,Rogers Ann,Shen Chan

Publisher

Elsevier BV

Reference33 articles.

1. 2022 American society for metabolic and bariatric surgery (ASMBS) and international federation for the surgery of obesity and metabolic disorders (IFSO): indications for metabolic and bariatric surgery;Eisenberg;Surg Obes Relat Dis,2022

2. Bariatric surgery survey 2018: similarities and disparities among the 5 IFSO chapters;Angrisani;Obes Surg,2021

3. Benefits and risks of bariatric surgery in adults: a review;Arterburn;JAMA,2020

4. Perioperative safety in the longitudinal assessment of bariatric surgery;Flum;N Engl J Med,2009

5. Long-Term outcomes after bariatric surgery: a systematic review and meta-analysis of weight loss at 10 or more years for all bariatric procedures and a single-centre review of 20-year outcomes after adjustable gastric banding;O'Brien;Obes Surg,2019

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