Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Appendicitis-II: Diagnostic Studies and Management

Appendicitis-II: Diagnostic Studies and Management

Diagnosing and managing appendicitis requires a structured and comprehensive approach that spans from initial assessment to postoperative care. Here is an overview of the process:
Diagnosing Appendicitis
It requires a multifaceted approach, starting with a detailed physical examination to pinpoint the location and nature of the pain and identify any associated symptoms. Laboratory tests play a crucial role. A complete Blood Count (CBC) typically reveals leukocytosis (an increased number of...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Colorectal dysplasia and malignancy outcomes in primary sclerosing cholangitis and inflammatory bowel disease requiring liver transplantation and colectomy: A multicenter study.

Surgery·2026

Same author

Evolution of the Morbidity and Mortality Conference in Surgery: From Codman to Contemporary Practice.

The American surgeon·2026

Same author

Artificial intelligence in rare pediatric solid tumor research and clinical care: A scoping review.

Journal of pediatric surgery·2026

Same author

Effectiveness of Adjunctive Measures to Limit Recurrence and Reoperation After Laparoscopic Repair of Large Paraesophageal Hernias: A Single-Institution Series.

Journal of clinical medicine·2026

Same author

The Role of Perioperative Artificial Intelligence in Colon and Rectal Surgery.

Clinics in colon and rectal surgery·2026

Same author

Insights From Michael Polanyi: Tacit Knowledge and Its Critical Importance in Medical Education.

Cureus·2026

Same journal

Predictors of 1-year weight maintenance after intragastric balloon removal: a real-world cohort study of 478 patients.

Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery·2026

Same journal

Late hiatal hernia after Roux-en-Y gastric bypass: a systematic review.

Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery·2026

Same journal

Comment on: The Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program's role in the evolution of quality in metabolic and bariatric surgery.

Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery·2026

Same journal

Paired editorial: Endoscopic septotomy with argon plasma coagulation (ES-APC) for the management of refractory postbariatric surgery fistulas and leaks (with video): results from a tertiary referral center.

Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery·2026

Same journal

Paired editorial: "The impact of obesity onset and duration on outcomes after metabolic bariatric surgery: an international multicenter cohort study".

Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery·2026

Same journal

Metabolic and bariatric surgery and risk of cardiac arrhythmias and mortality in severe obesity: a multicenter real-world propensity-matched study.

Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jul 23, 2025

Sleeve Gastrectomy in Mice using Surgical Clips

Sleeve Gastrectomy in Mice using Surgical Clips

Published on: November 14, 2020

Predicting readmission after bariatric surgery using machine learning.

Logan R Butler¹, Kevin A Chen¹, Justin Hsu¹

¹Department of Surgery, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina.

Surgery for Obesity and Related Diseases : Official Journal of the American Society for Bariatric Surgery

|July 16, 2023

Summary

This summary is machine-generated.

Machine learning models significantly outperform logistic regression in predicting 30-day readmissions after bariatric surgery. These advanced algorithms can identify high-risk patients for targeted interventions and resource allocation.

Keywords:

Bariatric surgery Machine learning Predictive modeling Readmission

More Related Videos

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

Single-Anastomosis Duodeno-Ileal Bypass with Sleeve Gastrectomy Model in Mice

Single-Anastomosis Duodeno-Ileal Bypass with Sleeve Gastrectomy Model in Mice

Published on: February 10, 2023

Related Experiment Videos

Last Updated: Jul 23, 2025

Sleeve Gastrectomy in Mice using Surgical Clips

Sleeve Gastrectomy in Mice using Surgical Clips

Published on: November 14, 2020

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

Published on: October 10, 2018

Single-Anastomosis Duodeno-Ileal Bypass with Sleeve Gastrectomy Model in Mice

Single-Anastomosis Duodeno-Ileal Bypass with Sleeve Gastrectomy Model in Mice

Published on: February 10, 2023

Area of Science:

Bariatric surgery outcomes
Predictive modeling in healthcare
Machine learning applications

Background:

Bariatric surgery is effective for weight loss but associated with costly readmissions.
Predicting postoperative readmissions is crucial for improving patient outcomes and reducing healthcare expenses.

Purpose of the Study:

To develop and compare machine learning (ML) algorithms for predicting 30-day readmissions post-bariatric surgery.
To evaluate the performance of ML models against traditional logistic regression.

Main Methods:

Utilized data from the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) database (2016-2020).
Analyzed patient variables using random forest (RF), gradient boosting (XGB), and deep neural networks (NN).
Compared predictive accuracy using area under the receiver operating characteristic curve (AUROC) against logistic regression (LR).

Main Results:

Included 863,348 patients; 4.52% experienced readmission.
XGB and RF models achieved AUROC scores of 0.785, significantly higher than LR's 0.62 (P < .001).
The best model (XGB) demonstrated 73.81% sensitivity and 70% specificity.

Conclusions:

Machine learning models offer a substantial improvement over logistic regression for predicting bariatric surgery readmissions.
Validated ML models can identify patients suitable for early discharge or requiring focused post-discharge support.