Gastroenterology

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

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Large-scale multi-center CT and MRI segmentation of pancreas with deep learning.

Automated volumetric segmentation of the pancreas on cross-sectional imaging is needed for diagnosis...

A multi-layer neural network approach for the stability analysis of the Hepatitis B model.

In the present study, we explore the dynamics of Hepatitis B virus infection, a significant global h...

Pred-AHCP: Robust Feature Selection-Enabled Sequence-Specific Prediction of Anti-Hepatitis C Peptides via Machine Learning.

Every year, an estimated 1.5 million people worldwide contract Hepatitis C, a significant contributo...

Deep learning in image segmentation for cancer.

This article discusses the role of deep learning (DL) in cancer imaging, focusing on its application...

Computed tomography enterography radiomics and machine learning for identification of Crohn's disease.

BACKGROUND: Crohn's disease is a severe chronic and relapsing inflammatory bowel disease. Although c...

Random survival forest algorithm for risk stratification and survival prediction in gastric neuroendocrine neoplasms.

This study aimed to construct and assess a machine-learning algorithm designed to forecast survival ...

A lightweight deep-learning model for parasite egg detection in microscopy images.

BACKGROUND: Intestinal parasitic infections are still a serious public health problem in developing ...

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

BACKGROUND: Although capsule endoscopy (CE) is a crucial tool for diagnosing small bowel diseases, t...

Evaluating the Efficacy of Deep Learning Reconstruction in Reducing Radiation Dose for Computer-Aided Volumetry for Liver Tumor: A Phantom Study.

OBJECTIVE: The purpose of this study was to compare radiation dose reduction capability for accurate...

Unbiased and reproducible liver MRI-PDFF estimation using a scan protocol-informed deep learning method.

OBJECTIVE: To estimate proton density fat fraction (PDFF) from chemical shift encoded (CSE) MR image...

A deep learning approach for gastroscopic manifestation recognition based on Kyoto Gastritis Score.

OBJECTIVE: The risk of gastric cancer can be predicted by gastroscopic manifestation recognition and...

Interpretable prediction of 30-day mortality in patients with acute pancreatitis based on machine learning and SHAP.

BACKGROUND: Severe acute pancreatitis (SAP) can be fatal if left unrecognized and untreated. The pur...

MCI Net: Mamba- Convolutional lightweight self-attention medical image segmentation network.

With the development of deep learning in the field of medical image segmentation, various network se...

Clinical validation of an AI-based pathology tool for scoring of metabolic dysfunction-associated steatohepatitis.

Metabolic dysfunction-associated steatohepatitis (MASH) is a major cause of liver-related morbidity ...

Artificial intelligence-aided colonoscopic differential diagnosis between Crohn's disease and gastrointestinal tuberculosis.

BACKGROUND AND AIM: Differentiating between Crohn's disease (CD) and gastrointestinal tuberculosis (...

A deep learning framework for hepatocellular carcinoma diagnosis using MS1 data.

Clinical proteomics analysis is of great significance for analyzing pathological mechanisms and disc...

A Multi-Task Based Deep Learning Framework With Landmark Detection for MRI Couinaud Segmentation.

To achieve precise Couinaud liver segmentation in preoperative planning for hepatic surgery, accommo...

Accuracy of machine learning in diagnosing microsatellite instability in gastric cancer: A systematic review and meta-analysis.

BACKGROUND: Significant challenges persist in the early identification of microsatellite instability...

Transformative artificial intelligence in gastric cancer: Advancements in diagnostic techniques.

Gastric cancer represents a significant global health challenge with elevated incidence and mortalit...

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