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Development of Machine Learning Models to Predict Postoperative GERD Symptom Resolution After Laparoscopic Nissen Fundoplication
Sponsor: Korea University Anam Hospital
Summary
This study aims to develop machine learning models to predict postoperative gastroesophageal reflux symptom resolution after laparoscopic Nissen fundoplication using Elastic Net regression and synthetic minority oversampling technique (SMOTE).
Official title: Development of Elastic Net Regression-SMOTE Models to Predict Postoperative Gastroesophageal Reflux Symptom Resolution After Laparoscopic Nissen Fundoplication
Key Details
Gender
All
Age Range
20 Years - Any
Study Type
OBSERVATIONAL
Enrollment
112
Start Date
2017-02-01
Completion Date
2025-08-31
Last Updated
2025-06-26
Healthy Volunteers
No
Interventions
Laparoscopic Nissen fundoplication
Laparoscopic Nissen fundoplication (LNF) is the most commonly performed anti-reflux surgery. LNF is performed in patients with GERD refractory to medication or those expected to require long-term medical treatment. During LNF, the fundus of the stomach is mobilized and wrapped 360 degrees around the lower esophagus to reinforce the lower esophageal sphincter (LES), preventing the reflux of gastric contents into the esophagus.
Locations (1)
Korea University Anam Hospital
Seoul, South Korea