Gastroenterology

A prospective and comparative study on improving the diagnostic accuracy of early gastric cancer based on deep convolutional neural network real-time diagnosis system (with video).

BACKGROUND: Endoscopic diagnosis of early gastric cancer (EGC) is a challenge. It is not clear whether deep convolutional neural network (DCNN) model could improve the endoscopists' diagnostic performance.

Development and validation of a machine learning-based prediction model for hepatorenal syndrome in liver cirrhosis patients using MIMIC-IV and eICU databases.

Hepatorenal syndrome (HRS) is a key contributor to poor prognosis in liver cirrhosis. This study aims to leverage the database to build a predictive model for early identification of high-risk patients. From two sizable public databases, we retrieved pertinent information about the cirrhosis patients' therapies, comorbidities, laboratory results, and demographics. Patients from the eICU database s...

A large histological images dataset of gastric cancer with tumour microenvironment annotation for AI.

Gastric cancer (GC) is the third leading cause of cancer death worldwide. Its clinical course varies considerably due to the highly heterogeneous tumo...

Artificial intelligence assisted risk prediction in organ transplantation: a UK Live-Donor Kidney Transplant Outcome Prediction tool.

Predicting the outcome of a kidney transplant involving a living donor advances donor decision-making donors for clinicians and patients. However, th...

S2P-Matching: Self-Supervised Patch-Based Matching Using Transformer for Capsule Endoscopic Images Stitching.

The Magnetically Controlled Capsule Endoscopy (MCCE) has a limited shooting range, resulting in capturing numerous fragmented images and an inability ...

Predicting postoperative adhesive small bowel obstruction in infants under 3 months with intestinal malrotation: a random forest approach.

OBJECTIVE: This study aimed to develop a predictive model using a random forest algorithm to determine the likelihood of postoperative adhesive small ...

Do people prefer AI-generated patient educational materials over traditional ones?

OBJECTIVE: This study aimed to assess people's preference between traditional and Artificial Intelligence (AI)-generated colon cancer staging Patient ...

Deep learning-based MVIT-MLKA model for accurate classification of pancreatic lesions: a multicenter retrospective cohort study.

BACKGROUND: Accurate differentiation between benign and malignant pancreatic lesions is critical for effective patient management. This study aimed to...

Classification of chicken Eimeria species through deep transfer learning models: A comparative study on model efficacy.

Eimeria is a protozoan parasite that causes coccidiosis in various animal species, especially in chickens, resulting in infections characterized by in...

Machine learning classification and biochemical characteristics in the real-time diagnosis of gastric adenocarcinoma using Raman spectroscopy.

This study aimed to identify biomolecular differences between benign gastric tissues (gastritis/intestinal metaplasia) and gastric adenocarcinoma and ...

Deep learning algorithms for predicting pathological complete response in MRI of rectal cancer patients undergoing neoadjuvant chemoradiotherapy: a systematic review.

PURPOSE: This systematic review examines the utility of deep learning algorithms in predicting pathological complete response (pCR) in rectal cancer p...

Natural Language Processing in Gastroenterology: Current Applications and Future Directions.

Natural language processing (NLP), a branch of artificial intelligence, has rapidly gained importance in health care for converting unstructured clini...

Role of Artificial Intelligence in the Detection and Management of Premalignant and Malignant Lesions of the Esophagus and Stomach.

The advent of artificial intelligence (AI) and deep learning algorithms, particularly convolutional neural networks, promises to address pitfalls, bri...

The Role of Artificial Intelligence for Advanced Endoscopy.

Artificial intelligence (AI) application in gastroenterology has grown in the last decade and continues to evolve very rapidly. Early promising result...

Artificial Intelligence in Endoscopy Quality Measures.

Quality of gastrointestinal endoscopy is a major determinant of its effectiveness. Artificial intelligence (AI) has the potential to enhance quality m...

Impact of Artificial Intelligence on Gastroenterology Trainee Education.

Artificial intelligence (AI) is transforming gastroenterology, particularly in endoscopy, which has a direct impact on trainees and their education. A...

Analyzing the relationship between gene expression and phenotype in space-flown mice using a causal inference machine learning ensemble.

Spaceflight has several detrimental effects on human and rodent health. For example, liver dysfunction is a common phenotype observed in space-flown r...

Endoscopic ultrasonography-based intratumoral and peritumoral machine learning ultrasomics model for predicting the pathological grading of pancreatic neuroendocrine tumors.

OBJECTIVES: The objective is to develop and validate intratumoral and peritumoral ultrasomics models utilizing endoscopic ultrasonography (EUS) to pre...

Bimodal In Situ Analyzer for Circular RNA in Extracellular Vesicles Combined with Machine Learning for Accurate Gastric Cancer Detection.

Circular RNAs in extracellular vesicles (EV-circRNAs) are gaining recognition as potential biomarkers for the diagnosis of gastric cancer (GC). Most c...

Synthesized colonoscopy dataset from high-fidelity virtual colon with abnormal simulation.

With the advent of the deep learning-based colonoscopy system, the need for a vast amount of high-quality colonoscopy image datasets for training is c...