AIMC Topic: Appendicitis
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Development and validation of automated three-dimensional convolutional neural network model for acute appendicitis diagnosis.
Scientific reports
Mar 5, 2025
Rapid, accurate preoperative imaging diagnostics of appendicitis are critical in surgical decisions of emergency care. This study developed a fully automated diagnostic framework using a 3D convolutional neural network (CNN) to identify appendicitis ...
Diagnosis of Acute Appendicitis with Machine Learning-Based Computer Tomography: Diagnostic Reliability and Role in Clinical Management.
Journal of laparoendoscopic & advanced surgical techniques. Part A
Feb 19, 2025
Acute appendicitis (AA) is a common surgical emergency affecting 7-8% of the population. Timely diagnosis and treatment are crucial for preventing serious morbidity and mortality. Diagnosis typically involves physical examination, laboratory tests, ...
Artificial intelligence for the diagnosis of pediatric appendicitis: A systematic review.
The American journal of emergency medicine
Feb 17, 2025
BACKGROUND: While acute appendicitis is the most frequent surgical emergency in children, its diagnosis remains complex. Artificial intelligence (AI) and machine learning (ML) tools have been employed to improve the accuracy of various diagnoses, inc...
Machine-learning-assisted Preoperative Prediction of Pediatric Appendicitis Severity.
Journal of pediatric surgery
Jan 13, 2025
PURPOSE: This study evaluates the effectiveness of machine learning (ML) algorithms for improving the preoperative diagnosis of acute appendicitis in children, focusing on the accurate prediction of the severity of disease.
Machine-learning based prediction of appendicitis for patients presenting with acute abdominal pain at the emergency department.
World journal of emergency surgery : WJES
Dec 23, 2024
BACKGROUND: Acute abdominal pain (AAP) constitutes 5-10% of all emergency department (ED) visits, with appendicitis being a prevalent AAP etiology often necessitating surgical intervention. The variability in AAP symptoms and causes, combined with th...
An Approach for Combining Clinical Judgment with Machine Learning to Inform Medical Decision Making: Analysis of Nonemergency Surgery Strategies for Acute Appendicitis in Patients with Multiple Long-Term Conditions.
Medical decision making : an international journal of the Society for Medical Decision Making
Oct 23, 2024
BACKGROUND: Machine learning (ML) methods can identify complex patterns of treatment effect heterogeneity. However, before ML can help to personalize decision making, transparent approaches must be developed that draw on clinical judgment. We develop...
Efficacy of automated machine learning models and feature engineering for diagnosis of equivocal appendicitis using clinical and computed tomography findings.
Scientific reports
Sep 30, 2024
This study evaluates the diagnostic efficacy of automated machine learning (AutoGluon) with automated feature engineering and selection (autofeat), focusing on clinical manifestations, and a model integrating both clinical manifestations and CT findi...
Accurate diagnosis of acute appendicitis in the emergency department: an artificial intelligence-based approach.
Internal and emergency medicine
Aug 21, 2024
The diagnosis of abdominal pain in emergency departments is challenging, and appendicitis is a common concern. Atypical symptoms often delay diagnosis. Although the Alvarado score aids in decision-making, its low specificity can lead to unnecessary s...
Construction of a clinical prediction model for complicated appendicitis based on machine learning techniques.
Scientific reports
Jul 16, 2024
Acute appendicitis is a typical surgical emergency worldwide and one of the common causes of surgical acute abdomen in the elderly. Accurately diagnosing and differentiating acute appendicitis can assist clinicians in formulating a scientific and rea...
Multicenter validation of an artificial intelligence (AI)-based platform for the diagnosis of acute appendicitis.
Surgery
Jun 22, 2024
BACKGROUND: The current scores used to help diagnose acute appendicitis have a "gray" zone in which the diagnosis is usually inconclusive. Furthermore, the universal use of CT scanning is limited because of the radiation hazards and/or limited resour...
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