AIMC Topic: Gastrointestinal Hemorrhage

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Validation of a Machine Learning Algorithm, EVendo, for Predicting Esophageal Varices in Hepatocellular Carcinoma.

Digestive diseases and sciences Jun 19, 2024
BACKGROUND: Treatment with atezolizumab and bevacizumab has become standard of care for advanced unresectable hepatocellular carcinoma (HCC) but carries an increased gastrointestinal bleeding risk. Therefore, patients are often required to undergo es...
Predictive Value of Tests Humans Esophageal and Gastric Varices Machine Learning Gastrointestinal Hemorrhage Algorithms Endoscopy, Digestive System Retrospective Studies Male Female Middle Aged Aged Liver Neoplasms Carcinoma, Hepatocellular
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Systematic review of machine learning models in predicting the risk of bleed/grade of esophageal varices in patients with liver cirrhosis: A comprehensive methodological analysis.

Journal of gastroenterology and hepatology Jun 17, 2024
Esophageal varices (EV) in liver cirrhosis carry high mortality risks. Traditional endoscopy, which is costly and subjective, prompts a shift towards machine learning (ML). This review critically evaluates ML applications in predicting bleeding risks...
Predictive Value of Tests Esophageal and Gastric Varices Gastrointestinal Hemorrhage Risk Humans Machine Learning Risk Assessment Liver Cirrhosis
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The 2023 top 10 list of endoscopy topics in medical publishing: an annual review by the American Society for Gastrointestinal Endoscopy Editorial Board.

Gastrointestinal endoscopy May 8, 2024
Using a systematic literature search of original articles published during 2023 in Gastrointestinal Endoscopy (GIE) and other high-impact medical and gastroenterology journals, the GIE Editorial Board of the American Society for Gastrointestinal Endo...
Endoscopic Mucosal Resection Societies, Medical Endoscopy, Gastrointestinal Periodicals as Topic Humans Colonic Polyps Artificial Intelligence Gastrointestinal Hemorrhage United States Publishing
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Validation of GPT-4 for clinical event classification: A comparative analysis with ICD codes and human reviewers.

Journal of gastroenterology and hepatology Apr 16, 2024
BACKGROUND AND AIM: Effective clinical event classification is essential for clinical research and quality improvement. The validation of artificial intelligence (AI) models like Generative Pre-trained Transformer 4 (GPT-4) for this task and comparis...
Artificial Intelligence Sensitivity and Specificity International Classification of Diseases Gastrointestinal Hemorrhage Humans
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Artificial Intelligence for Identification of Images with Active Bleeding in Mesenteric and Celiac Arteries Angiography.

Cardiovascular and interventional radiology Mar 26, 2024
PURPOSE: The purpose of this study is to evaluate the efficacy of an artificial intelligence (AI) model designed to identify active bleeding in digital subtraction angiography images for upper gastrointestinal bleeding.
Middle Aged Radiographic Image Interpretation, Computer-Assisted Embolization, Therapeutic Celiac Artery Aged Adult Sensitivity and Specificity Male Gastrointestinal Hemorrhage Angiography, Digital Subtraction Mesenteric Arteries Humans Artificial Intelligence Algorithms Retrospective Studies Female
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Upper gastrointestinal haemorrhage patients' survival: A causal inference and prediction study.

European journal of clinical investigation Feb 20, 2024
BACKGROUND: Upper gastrointestinal (GI) bleeding is a common medical emergency. This study aimed to develop models to predict critically ill patients with upper GI bleeding in-hospital and 30-day survival, identify the correlation factor and infer th...
Gastrointestinal Hemorrhage Organ Dysfunction Scores Glasgow Coma Scale Length of Stay Hospital Mortality Causality Bilirubin Aged Male Middle Aged Humans Prognosis Machine Learning Critical Illness Algorithms Intensive Care Units Female
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Achieving Value by Risk Stratification With Machine Learning Model or Clinical Risk Score in Acute Upper Gastrointestinal Bleeding: A Cost Minimization Analysis.

The American journal of gastroenterology Nov 23, 2023
INTRODUCTION: We estimate the economic impact of applying risk assessment tools to identify very low-risk patients with upper gastrointestinal bleeding who can be safely discharged from the emergency department using a cost minimization analysis.
Costs and Cost Analysis Risk Assessment Severity of Illness Index Acute Disease Gastrointestinal Hemorrhage Humans Machine Learning Risk Factors
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Application of machine learning to predict postoperative gastrointestinal bleed in bariatric surgery.

Surgical endoscopy Jun 13, 2023
BACKGROUND: Postoperative gastrointestinal bleeding (GIB) is a rare but serious complication of bariatric surgery. The recent rise in extended venous thromboembolism regimens as well as outpatient bariatric surgery may increase the risk of postoperat...
Humans Machine Learning Retrospective Studies Logistic Models Postoperative Hemorrhage Bariatric Surgery Gastrointestinal Hemorrhage
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Comparative Effectiveness of Machine Learning Approaches for Predicting Gastrointestinal Bleeds in Patients Receiving Antithrombotic Treatment.

JAMA network open May 3, 2021
IMPORTANCE: Anticipating the risk of gastrointestinal bleeding (GIB) when initiating antithrombotic treatment (oral antiplatelets or anticoagulants) is limited by existing risk prediction models. Machine learning algorithms may result in superior pre...
Myocardial Ischemia Thienopyridines Female Aged Aged, 80 and over Atrial Fibrillation Risk Assessment Young Adult Venous Thromboembolism Adolescent Humans Antifibrinolytic Agents Cohort Studies Adult Machine Learning Predictive Value of Tests United States Gastrointestinal Hemorrhage Cross-Sectional Studies Retrospective Studies Fibrinolytic Agents Male Clinical Decision-Making Anticoagulants Middle Aged
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Neural network predicts need for red blood cell transfusion for patients with acute gastrointestinal bleeding admitted to the intensive care unit.

Scientific reports Apr 23, 2021
Acute gastrointestinal bleeding is the most common gastrointestinal cause for hospitalization. For high-risk patients requiring intensive care unit stay, predicting transfusion needs during the first 24 h using dynamic risk assessment may improve res...
Adult Female Humans Male Cohort Studies Reproducibility of Results Neural Networks, Computer Middle Aged Gastrointestinal Hemorrhage Aged Intensive Care Units Risk Assessment Patient Admission Aged, 80 and over Erythrocyte Transfusion
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