AI Medical Compendium Journal:
BMC gastroenterology

Showing 11 to 20 of 33 articles

Explainable machine learning model for predicting acute pancreatitis mortality in the intensive care unit.

BMC gastroenterology
BACKGROUND: Current prediction models are suboptimal for determining mortality risk in patients with acute pancreatitis (AP); this might be improved by using a machine learning (ML) model. In this study, we aimed to construct an explainable ML model ...

Machine learning for temporary stoma after intestinal resection in surgical decision-making of Crohn's disease.

BMC gastroenterology
BACKGROUND: Crohn's disease (CD) often necessitates surgical intervention, with temporary stoma creation after intestinal resection (IR) being a crucial decision. This study aimed to construct novel models based on machine learning (ML) to predict te...

Machine learning-based plasma metabolomics for improved cirrhosis risk stratification.

BMC gastroenterology
BACKGROUND: Cirrhosis is a leading cause of mortality in patients with chronic liver disease (CLD). The rapid development of metabolomic technologies has enabled the capture of metabolic changes related to the progression of cirrhosis.

A foundation systematic review of natural language processing applied to gastroenterology & hepatology.

BMC gastroenterology
OBJECTIVE: This review assesses the progress of NLP in gastroenterology to date, grades the robustness of the methodology, exposes the field to a new generation of authors, and highlights opportunities for future research.

Establishing an AI model and application for automated capsule endoscopy recognition based on convolutional neural networks (with video).

BMC gastroenterology
BACKGROUND: Although capsule endoscopy (CE) is a crucial tool for diagnosing small bowel diseases, the need to process a vast number of images imposes a significant workload on physicians, leading to a high risk of missed diagnoses. This study aims t...

Construction of a combined prognostic model for pancreatic ductal adenocarcinoma based on deep learning and digital pathology images.

BMC gastroenterology
BACKGROUND: Deep learning has made significant advancements in the field of digital pathology, and the integration of multiple models has further improved accuracy. In this study, we aimed to construct a combined prognostic model using deep learning-...

Development and application of an artificial intelligence-assisted endoscopy system for diagnosis of Helicobacter pylori infection: a multicenter randomized controlled study.

BMC gastroenterology
BACKGROUND: The early diagnosis and treatment of Heliobacter pylori (H.pylori) gastrointestinal infection provide significant benefits to patients. We constructed a convolutional neural network (CNN) model based on an endoscopic system to diagnose H....

Improved diagnostic efficiency of CRC subgroups revealed using machine learning based on intestinal microbes.

BMC gastroenterology
BACKGROUND: Colorectal cancer (CRC) is a common cancer that causes millions of deaths worldwide each year. At present, numerous studies have confirmed that intestinal microbes play a crucial role in the process of CRC. Additionally, studies have show...

Meta-analysis of the effectiveness of early endoscopic treatment of Acute biliary pancreatitis based on lightweight deep learning model.

BMC gastroenterology
BACKGROUND: Acute biliary pancreatitis (ABP) is a clinical common acute abdomen. After the first pancreatitis, relapse rate is high, which seriously affects human life and health and causes great economic burdens to family and society. According to a...