Gastroenterology

Impact of Artificial Intelligence on the Timing of Recurrent Laryngeal Nerve Recognition during Robot-Assisted Minimally Invasive Esophagectomy.

BACKGROUND: As a first step to prevent recurrent laryngeal nerve (RLN) palsy, we have developed an a...

Corrigendum to "SHapley Additive exPlanations (SHAP)-based, multivariate machine-learning techniques with external validation: Construction of a preoperative interpretable predictive model for intestinal resection of incarcerated inguinal hernia" [Surgery 184 (2025) 109406].

Diagnostic Performance of Radiomics for Differentiating Intrahepatic Cholangiocarcinoma from Hepatocellular Carcinoma: A Systematic Review and Meta-analysis.

BACKGROUND: Differentiating intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC...

AI-based CT assessment of sarcopenia in borderline resectable pancreatic Cancer: A narrative review of clinical and technical perspectives.

BACKGROUND: Sarcopenia, defined as the progressive loss of skeletal muscle mass and function, has be...

A hybrid multi-instance learning-based identification of gastric adenocarcinoma differentiation on whole-slide images.

OBJECTIVE: To investigate the potential of a hybrid multi-instance learning model (TGMIL) combining ...

Artificial Intelligence-Powered Spatial Analysis of Immune Phenotypes in Resected Pancreatic Cancer.

IMPORTANCE: Although tumor-infiltrating lymphocytes (TILs) have been implicated as prognostic biomar...

The impact of artificial intelligence on the adenoma detection rate : Comparison between experienced, intermediate and trainee endoscopists' adenoma detection rate.

BACKGROUND: Artificial intelligence (AI) is a promising tool to achieve a high adenoma detection rat...

[The application of artificial intelligence in enhancing the safety of pancreatic surgeries].

Pancreatic surgeries have long been considered as challenging procedures due to its complex surgical...

[Current situation and development trends of minimally invasive surgical procedures in the treatment of pancreatic tumors].

With the rapid development of modern medical technology,minimally invasive surgical procedures are p...

How appropriately can generative artificial intelligence platforms, including GPT-4, Gemini, Bing, and Wrtn, answer questions about colon cancer in the Korean language?

PURPOSE: This study aims to assess the performance of 4 generative artificial intelligence (AI) plat...

Machine learning prediction of intestinal α-glucosidase inhibitors using a diverse set of ligands: a drug repurposing effort with drugBank database screening.

UNLABELLED: The global rise in diabetes mellitus (DM) poses a significant health challenge, necessit...

The liver reconditioning in critical care medicine.

PURPOSE OF REVIEW: Machine perfusion has emerged as a transformative alternative to static cold stor...

AI-based large-scale screening of gastric cancer from noncontrast CT imaging.

Early detection through screening is critical for reducing gastric cancer (GC) mortality. However, i...

Preoperative Assessment of Lymph Node Metastasis in Rectal Cancer Using Deep Learning: Investigating the Utility of Various MRI Sequences.

PURPOSE: This study aimed to develop a deep learning (DL) model based on three-dimensional multi-par...

Machine learning model for the prediction of postoperative acute kidney injury (AKI) in neonates undergoing digestive surgery.

OBJECTIVE: The aim of our study is to determine the main predictors of postoperative AKI in neonates...

Validation of a Pretrained Artificial Intelligence Model for Pancreatic Cancer Detection on Diagnosis and Prediagnosis Computed Tomography Scans.

PURPOSE: To evaluate PANCANAI, a previously developed AI model for pancreatic cancer (PC) detection,...

DeepSeek-assisted LI-RADS classification: AI-driven precision in hepatocellular carcinoma diagnosis.

BACKGROUND: The clinical utility of the DeepSeek-V3 (DSV3) model in enhancing the accuracy of Liver ...

Comments on "Integrating machine learning and molecular docking to decipher the molecular network of aflatoxin B1-induced hepatocellular carcinoma".

Machine Learning Models Based on CT Enterography for Differentiating Between Ulcerative Colitis and Colonic Crohn's Disease Using Intestinal Wall, Mesenteric Fat, and Visceral Fat Features.

PURPOSE: This study aimed to develop radiomic-based machine learning models using computed tomograph...

Harnessing the machine learning and nomogram models: elevating prognostication in nonmetastatic gastric cancer with "double invasion" for personalized patient care.

OBJECTIVE: To develop and validate a machine learning framework combined with a nomogram for predict...

Association rule mining of the human gut microbiome.

The human gut carries a vast and diverse microbial community that is essential for human health. Und...