Gastroenterology

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

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Origami-Inspired Bionic Soft Robot Stomach with Self-Powered Sensing.

The stomach is a vital organ in the human digestive system, and its digestive condition is critical ...

Robust and consistent biomarker candidates identification by a machine learning approach applied to pancreatic ductal adenocarcinoma metastasis.

BACKGROUND: Machine Learning (ML) plays a crucial role in biomedical research. Nevertheless, it stil...

A deep learning-powered diagnostic model for acute pancreatitis.

BACKGROUND: Acute pancreatitis is one of the most common diseases requiring emergency surgery. Rapid...

Diagnosis to dissection: AI's role in early detection and surgical intervention for gastric cancer.

Gastric cancer remains a formidable health challenge worldwide; early detection and effective surgic...

A Machine Learning Algorithm Avoids Unnecessary Paracentesis for Exclusion of SBP in Cirrhosis in Resource-limited Settings.

BACKGROUND & AIMS: Despite the poor prognosis associated with missed or delayed spontaneous bacteria...

Machine Learning-Based Models for Advanced Fibrosis and Cirrhosis Diagnosis in Chronic Hepatitis B Patients With Hepatic Steatosis.

BACKGROUND AND AIMS: The global rise of chronic hepatitis B (CHB) superimposed on hepatic steatosis ...

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

BACKGROUND: Treatment with atezolizumab and bevacizumab has become standard of care for advanced unr...

Identification of hepatic steatosis among persons with and without HIV using natural language processing.

BACKGROUND: Steatotic liver disease (SLD) is a growing phenomenon, and our understanding of its dete...

Noninvasive prediction of lymph node metastasis in pancreatic cancer using an ultrasound-based clinicoradiomics machine learning model.

OBJECTIVES: This study was designed to explore and validate the value of different machine learning ...

Non-Invasive Detection of Early-Stage Fatty Liver Disease via an On-Skin Impedance Sensor and Attention-Based Deep Learning.

Early-stage nonalcoholic fatty liver disease (NAFLD) is a silent condition, with most cases going un...

A machine learning model based on clinical features and ultrasound radiomics features for pancreatic tumor classification.

OBJECTIVE: This study aimed to construct a machine learning model using clinical variables and ultra...

UDBRNet: A novel uncertainty driven boundary refined network for organ at risk segmentation.

Organ segmentation has become a preliminary task for computer-aided intervention, diagnosis, radiati...

Diagnostic accuracy of CT-based radiomics and deep learning for predicting lymph node metastasis in esophageal cancer.

BACKGROUND: Esophageal cancer remains a global challenge due to late diagnoses and limited treatment...

A deep-learning-based model for assessment of autoimmune hepatitis from histology: AI(H).

Histological assessment of autoimmune hepatitis (AIH) is challenging. As one of the possible results...

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