Gastroenterology

Latest AI and machine learning research in gastroenterology for healthcare professionals.

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Radiomics machine learning algorithm facilitates detection of small pancreatic neuroendocrine tumors on CT.

PURPOSE: The purpose of this study was to develop a radiomics-based algorithm to identify small panc...

Machine learning predicts acute respiratory failure in pancreatitis patients: A retrospective study.

PURPOSE: The purpose of the research is to design an algorithm to predict the occurrence of acute re...

AI in obstetrics: Evaluating residents' capabilities and interaction strategies with ChatGPT.

In line with the digital transformation trend in medical training, students may resort to artificial...

Multitask machine learning-based tumor-associated collagen signatures predict peritoneal recurrence and disease-free survival in gastric cancer.

BACKGROUND: Accurate prediction of peritoneal recurrence for gastric cancer (GC) is crucial in clini...

Immunohistochemistry annotations enhance AI identification of lymphocytes and neutrophils in digitized H&E slides from inflammatory bowel disease.

BACKGROUND AND OBJECTIVE: Histologic assessment of the immune infiltrate in H&E slides is vital in d...

Systems Biology and Machine Learning Identify Genetic Overlaps Between Lung Cancer and Gastroesophageal Reflux Disease.

One Health and planetary health place emphasis on the common molecular mechanisms that connect sever...

Gemini-Assisted Deep Learning Classification Model for Automated Diagnosis of High-Resolution Esophageal Manometry Images.

To develop a deep learning model for esophageal motility disorder diagnosis using high-resolution m...

Usefulness of an Artificial Intelligence Model in Recognizing Recurrent Laryngeal Nerves During Robot-Assisted Minimally Invasive Esophagectomy.

BACKGROUND: Recurrent laryngeal nerve (RLN) palsy is a common complication in esophagectomy and its ...

Evaluation of floatability characteristics of gastroretentive tablets using VIS imaging with artificial neural networks.

Gastroretentive dosage forms are recommended for several active substances because it is often neces...

Advanced Prediction of Hepatic Oncogenic Transformation in HBV Patients via RNA-Seq Data Analysis and Deep Learning Techniques.

Liver cancer, recognized as a significant global health issue, is increasingly correlated with Hepat...

A Predictive Model of Pressure Injury in Children Undergoing Living Donor Liver Transplantation Based on Machine Learning Algorithm.

AIMS: The aim of our study was to formulate and validate a prediction model using machine learning a...

A Machine Learning-Driven Surface-Enhanced Raman Scattering Analysis Platform for the Label-Free Detection and Identification of Gastric Lesions.

BACKGROUND: Gastric lesions pose significant clinical challenges due to their varying degrees of mal...

Precise ablation zone segmentation on CT images after liver cancer ablation using semi-automatic CNN-based segmentation.

BACKGROUND: Ablation zone segmentation in contrast-enhanced computed tomography (CECT) images enable...

A Multi-Scale Liver Tumor Segmentation Method Based on Residual and Hybrid Attention Enhanced Network with Contextual Integration.

Liver cancer is one of the malignancies with high mortality rates worldwide, and its timely detectio...

A time-dependent explainable radiomic analysis from the multi-omic cohort of CPTAC-Pancreatic Ductal Adenocarcinoma.

BACKGROUND AND OBJECTIVE: In Pancreatic Ductal Adenocarcinoma (PDA), multi-omic models are emerging ...

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