Gastroenterology

Pairwise machine learning-based automatic diagnostic platform utilizing CT images and clinical information for predicting radiotherapy locoregional recurrence in elderly esophageal cancer patients.

OBJECTIVE: To investigate the feasibility and accuracy of predicting locoregional recurrence (LR) in...

Deep Learning-Based Approach for Identifying and Measuring Focal Liver Lesions on Contrast-Enhanced MRI.

BACKGROUND: The number of focal liver lesions (FLLs) detected by imaging has increased worldwide, hi...

Identifying patients with undiagnosed small intestinal neuroendocrine tumours in primary care using statistical and machine learning: model development and validation study.

BACKGROUND: Neuroendocrine tumours (NETs) are increasing in incidence, often diagnosed at advanced s...

A knowledge-enhanced interpretable network for early recurrence prediction of hepatocellular carcinoma via multi-phase CT imaging.

BACKGROUND: Predicting early recurrence (ER) of hepatocellular carcinoma (HCC) accurately can guide ...

Deep Learning for Histopathological Assessment of Esophageal Adenocarcinoma Precursor Lesions.

Histopathological assessment of esophageal biopsies is a key part in the management of patients with...

Deep learning for 3D biliary anatomy for living liver donor hepatectomy planning.

Optimizing large language models in digestive disease: strategies and challenges to improve clinical outcomes.

Large Language Models (LLMs) are transformer-based neural networks with billions of parameters train...

Deep Learning-Based Segmentation and Risk Stratification for Gastrointestinal Stromal Tumors in Transabdominal Ultrasound Imaging.

PURPOSE: To develop a deep neural network system for the automatic segmentation and risk stratificat...

Development of UroSAM: A Machine Learning Model to Automatically Identify Kidney Stone Composition from Endoscopic Video.

Chemical composition analysis is important in prevention counseling for kidney stone disease. Advan...

Development of a diagnostic support system for the fibrosis of nonalcoholic fatty liver disease using artificial intelligence and deep learning.

Liver fibrosis is a pathological condition characterized by the abnormal proliferation of liver tiss...

Early prediction of acute gallstone pancreatitis severity: a novel machine learning model based on CT features and open access online prediction platform.

BACKGROUND: Early diagnosis of acute gallstone pancreatitis severity (GSP) is challenging in clinica...

Enhancing liver fibrosis diagnosis and treatment assessment: a novel biomechanical markers-based machine learning approach.

Accurate diagnosis and treatment assessment of liver fibrosis face significant challenges, including...

Automated machine learning for predicting liver metastasis in patients with gastrointestinal stromal tumor: a SEER-based analysis.

Gastrointestinal stromal tumors (GISTs) are a rare type of tumor that can develop liver metastasis (...

Machine Learning Identifies Key Proteins in Primary Sclerosing Cholangitis Progression and Links High CCL24 to Cirrhosis.

Primary sclerosing cholangitis (PSC) is a rare, progressive disease, characterized by inflammation a...

Liver respiratory-induced motion estimation using abdominal surface displacement as a surrogate: robotic phantom and clinical validation with varied correspondence models.

PURPOSE: This work presents the implementation of an RGB-D camera as a surrogate signal for liver re...

Deep learning model for differentiating nasal cavity masses based on nasal endoscopy images.

BACKGROUND: Nasal polyps and inverted papillomas often look similar. Clinically, it is difficult to ...

Predicting Non-Alcoholic Steatohepatitis: A Lipidomics-Driven Machine Learning Approach.

Nonalcoholic fatty liver disease (NAFLD), nowadays the most prevalent chronic liver disease in Weste...

Automated Endoscopic Diagnosis in IBD: The Emerging Role of Artificial Intelligence.

The emerging role of artificial intelligence (AI) in automated endoscopic diagnosis represents a sig...

Deep Learning Based Cystoscopy Image Enhancement.

Endoscopy image enhancement technology provides doctors with clearer and more detailed images for o...

Light&fast generative adversarial network for high-fidelity CT image synthesis of liver tumor.

BACKGROUND AND OBJECTIVE: Hepatocellular carcinoma is a common disease with high mortality. Through ...

A novel risk scoring system predicts overall survival of hepatocellular carcinoma using cox proportional hazards machine learning method.

BACKGROUND: Robust and practical prognosis prediction models for hepatocellular carcinoma (HCC) pati...