Peptic Ulcer Disease

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 endoscopy images, which are difficult to be captured. By analyzing the differences between the internal and external features of the lesion area, we propose a lesion-decoupling-based segmentation (LDS) network for assisting early cancer diagnosis. We introduce a plug-and-play module called self-sampling si...

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. Existing diagnostic techniques are often invasive and carry risks of complications. Herein, we introduce a plasmonic gold nanopolyhedron (AuNH)-coated needle-based surface-enhanced Raman scattering (SERS) sensor, integrated with endoscopy, for direct mucus sampling and label-free detection of CRC. T...

DGCPPISP: a PPI site prediction model based on dynamic graph convolutional network and two-stage transfer learning.

BACKGROUND: Proteins play a pivotal role in the diverse array of biological processes, making the precise prediction of protein-protein interaction (P...

Machine learning identifies key cells and therapeutic targets during ferroptosis after spinal cord injury.

JOURNAL/nrgr/04.03/01300535-202606000-00064/figure1/v/2026-02-11T151048Z/r/image-tiff Ferroptosis, a type of cell death that mainly involves iron meta...

Endoscopic Artificial Intelligence for Image Analysis in Gastrointestinal Neoplasms.

BACKGROUND: Artificial intelligence (AI) using deep learning systems has recently been utilized in various medical fields. In the field of gastroenter...

Potential Shared Mitochondrial-Related Gene Signatures and Molecular Mechanisms Between Polycystic Ovary Syndrome (PCOS) and Major Depressive Disorder (MDD): Evidence from Transcriptome Data and Machine Learning.

Polycystic ovary syndrome (PCOS) is strongly associated with major depressive disorder (MDD), but the shared pathophysiological mechanisms between the...

An artificial intelligence-assisted system versus white light endoscopy alone for adenoma detection in individuals with Lynch syndrome (TIMELY): an international, multicentre, randomised controlled trial.

BACKGROUND: Computer-aided detection (CADe) systems for colonoscopy have been shown to increase small polyp detection during colonoscopy in the genera...

Development of a machine learning approach for prediction of red blood cell transfusion in patients undergoing Cesarean section at a single institution.

Despite recent advances in surgical techniques and perinatal management in obstetrics for reducing intraoperative bleeding, blood transfusion may occu...

Using Machine Learning for Endoscopic Detection of Low-Grade Subglottic Stenosis: A Proof of Principle.

The current study trains, tests, and evaluates a deep learning algorithm to detect subglottic stenosis (SGS) on endoscopy. A retrospective review of p...

Automated Method for Intracranial Aneurysm Classification Using Deep Learning.

Intracranial aneurysm (IA) is now a common term closely associated with subarachnoid hemorrhage. IA is the bulging of a blood vessel caused by a weake...

Artificial intelligence for automatic detection and segmentation of nasal polyposis: a pilot study.

PURPOSE: Accurate diagnosis and quantification of polyps and symptoms are pivotal for planning the therapeutic strategy of Chronic rhinosinusitis with...

Establishment of a corneal ulcer prognostic model based on machine learning.

Corneal infection is a major public health concern worldwide and the most common cause of unilateral corneal blindness. Toxic effects of different mic...

How Artificial Intelligence Will Transform Clinical Care, Research, and Trials for Inflammatory Bowel Disease.

Artificial intelligence (AI) refers to computer-based methodologies that use data to teach a computer to solve pre-defined tasks; these methods can be...

Optimizing cystoscopy and TURBT: enhanced imaging and artificial intelligence.

Diagnostic cystoscopy in combination with transurethral resection of the bladder tumour are the standard for the diagnosis, surgical treatment and sur...

Computer Vision and Videomics in Otolaryngology-Head and Neck Surgery: Bridging the Gap Between Clinical Needs and the Promise of Artificial Intelligence.

This article discusses the role of computer vision in otolaryngology, particularly through endoscopy and surgery. It covers recent applications of art...

A deep learning-driven discovery of berberine derivatives as novel antibacterial against multidrug-resistant Helicobacter pylori.

Helicobacter pylori (H. pylori) is currently recognized as the primary carcinogenic pathogen associated with gastric tumorigenesis, and its high preva...

Validation of an Electronic Health Record-Based Machine Learning Model Compared With Clinical Risk Scores for Gastrointestinal Bleeding.

BACKGROUND & AIMS: Guidelines recommend use of risk stratification scores for patients presenting with gastrointestinal bleeding (GIB) to identify ver...

Comprehensive Bioinformatics Analysis and Machine Learning of TTK as a Transhepatic Arterial Chemoembolization Resistance Target in Hepatocellular Carcinoma.

Transhepatic arterial chemoembolization (TACE) is the standard treatment for intermediate-stage hepatocellular carcinoma (HCC). However, a significant...

A Hierarchical Graph Neural Network Framework for Predicting Protein-Protein Interaction Modulators With Functional Group Information and Hypergraph Structure.

Accurate prediction of small molecule modulators targeting protein-protein interactions (PPIMs) remains a significant challenge in drug discovery. Exi...

Machine Learning-Driven SERS Nanoendoscopy and Optophysiology.

A frontier of analytical sciences is centered on the continuous measurement of molecules in or near cells, tissues, or organs, within the biological c...