Gastroenterology

Preoperative prediction of rectal Cancer staging combining MRI deep transfer learning, radiomics features, and clinical factors: accurate differentiation from stage T2 to T3.

BACKGROUND: This study evaluates the efficacy of integrating MRI deep transfer learning, radiomic si...

Lesion-Decoupling-Based Segmentation With Large-Scale Colon and Esophageal Datasets for Early Cancer Diagnosis.

Lesions of early cancers often show flat, small, and isochromatic characteristics in medical endosco...

Linked Color Imaging with Artificial Intelligence Improves the Detection of Early Gastric Cancer.

INTRODUCTION: Esophagogastroduodenoscopy is the most important tool to detect gastric cancer (GC). I...

Machine learning-assisted label-free colorectal cancer diagnosis using plasmonic needle-endoscopy system.

Early and accurate detection of colorectal cancer (CRC) is critical for improving patient outcomes. ...

Integrating Deep Learning-Based Dose Distribution Prediction with Bayesian Networks for Decision Support in Radiotherapy for Upper Gastrointestinal Cancer.

PURPOSE: Selecting the better techniques to harbor optimal motion management, either a stereotactic ...

Artificial intelligence for surgical safety during laparoscopic gastrectomy for gastric cancer: Indication of anatomical landmarks related to postoperative pancreatic fistula using deep learning.

BACKGROUND: Postoperative pancreatic fistula (POPF) is a critical complication of laparoscopic gastr...

Deep learning is necessary for safety regulation in predicting malnutrition in gastric cancer patients.

Integrated machine learning screened glutamine metabolism-associated biomarker SLC1A5 to predict immunotherapy response in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) stands as one of the most prevalent malignancies. While PD-1 immune c...

Integrating bioinformatics and machine learning methods to analyze diagnostic biomarkers for HBV-induced hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a malignant tumor. It is estimated that approximately 50-80% of HC...

Deep learning predicts the 1-year prognosis of pancreatic cancer patients using positive peritoneal washing cytology.

Peritoneal washing cytology (CY) in patients with pancreatic cancer is mainly used for staging; howe...

Identification of histopathological classification and establishment of prognostic indicators of gastric adenocarcinoma based on deep learning algorithm.

The aim of this study is to establish a deep learning (DL) model to predict the pathological type of...

Optimizing post-transplantation outcomes: the role of multi-omics, artificial intelligence, and animal models in addressing immunosuppression-associated hepatotoxicity.

Letter to the Editor: commentary on 'Artificial intelligence-based diagnosis of standard endoscopic ultrasonography scanning sites in the biliopancreatic system: a multicenter retrospective study'.

Application Value of the Automated Machine Learning Model Based on Modified Computed Tomography Severity Index Combined With Serological Indicators in the Early Prediction of Severe Acute Pancreatitis.

BACKGROUND AND AIMS: Machine learning (ML) algorithms are widely applied in building models of medic...

Machine Learning Predicts Patients With New-onset Diabetes at Risk of Pancreatic Cancer.

BACKGROUND: New-onset diabetes represent a high-risk cohort to screen for pancreatic cancer.

Combined structure-based virtual screening and machine learning approach for the identification of potential dual inhibitors of ACC and DGAT2.

Acetyl-coenzyme A carboxylase (ACC) and diacylglycerol acyltransferase 2 (DGAT2) are recognized as p...

The potential of an artificial intelligence for diagnosing MRI images in rectal cancer: multicenter collaborative trial.

BACKGROUND: An artificial intelligence-based algorithm we developed, mrAI, satisfactorily segmented ...

Machine learning uncovers manganese as a key nutrient associated with reduced risk of steatotic liver disease.

BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects approximately 2...

Optimizing adjuvant treatment strategies for non-pancreatic periampullary cancers.

Non-pancreatic periampullary tumors have long been neglected, leading to blurred adjuvant treatment ...

Machine learning-based screening and validation of liver metastasis-specific genes in colorectal cancer.

Colorectal liver metastasis (CRLM) is challenging in the clinical treatment of colorectal cancer. Li...

Development and validation of a machine learning-based F-fluorodeoxyglucose PET/CT radiomics signature for predicting gastric cancer survival.

BACKGROUND: Survival prognosis of patients with gastric cancer (GC) often influences physicians' cho...