Gastroenterology

Peptic Ulcer Disease

Latest AI and machine learning research in peptic ulcer disease for healthcare professionals.

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Showing 190-210 of 3,581 articles
Protein-protein interaction detection using deep learning: A survey, comparative analysis, and experimental evaluation.

This survey paper provides a comprehensive analysis of various Deep Learning (DL) techniques and alg...

MDMNI-DGD: A novel graph neural network approach for druggable gene discovery based on the integration of multi-omics data and the multi-view network.

Accurately predicting druggable genes is of paramount importance for enhancing the efficacy of targe...

Automated Detection of Gastrointestinal Diseases Using Resnet50*-Based Explainable Deep Feature Engineering Model with Endoscopy Images.

This work aims to develop a novel convolutional neural network (CNN) named ResNet50* to detect vario...

Toward automated small bowel capsule endoscopy reporting using a summarizing machine learning algorithm: The SUM UP study.

BACKGROUND AND OBJECTIVES: Deep learning (DL) algorithms demonstrate excellent diagnostic performanc...

Computer tomography-based radiomics combined with machine learning for predicting the time since onset of epidural hematoma.

Estimation of the age of epidural hematoma (EDH) is a challenge in clinical forensic medicine, and t...

ProAffinity-GNN: A Novel Approach to Structure-Based Protein-Protein Binding Affinity Prediction via a Curated Data Set and Graph Neural Networks.

Protein-protein interactions (PPIs) are crucial for understanding biological processes and disease m...

Deep learning-based automatic bleeding recognition during liver resection in laparoscopic hepatectomy.

BACKGROUND: Intraoperative hemorrhage during laparoscopic hepatectomy (LH) is a risk factor for nega...

An experimental analysis of graph representation learning for Gene Ontology based protein function prediction.

Understanding protein function is crucial for deciphering biological systems and facilitating variou...

Protein-Protein Interaction Networks Derived from Classical and Machine Learning-Based Natural Language Processing Tools.

The study of protein-protein interactions (PPIs) provides insight into various biological mechanisms...

Graph-based machine learning model for weight prediction in protein-protein networks.

Proteins interact with each other in complex ways to perform significant biological functions. These...

Integration of molecular coarse-grained model into geometric representation learning framework for protein-protein complex property prediction.

Structure-based machine learning algorithms have been utilized to predict the properties of protein-...

Establishing an AI model and application for automated capsule endoscopy recognition based on convolutional neural networks (with video).

BACKGROUND: Although capsule endoscopy (CE) is a crucial tool for diagnosing small bowel diseases, t...

G-Protein Signaling in Alzheimer's Disease: Spatial Expression Validation of Semi-supervised Deep Learning-Based Computational Framework.

Systemic study of pathogenic pathways and interrelationships underlying genes associated with Alzhei...

Exploration of common pathogenesis and candidate hub genes between HIV and monkeypox co-infection using bioinformatics and machine learning.

This study explored the pathogenesis of human immunodeficiency virus (HIV) and monkeypox co-infectio...

Key genes and pathways in the molecular landscape of pancreatic ductal adenocarcinoma: A bioinformatics and machine learning study.

Pancreatic ductal adenocarcinoma (PDAC) is recognized for its aggressive nature, dismal prognosis, a...

Patient public perspectives on digital colorectal cancer surgery (DALLAS).

INTRODUCTION: The importance of patient perspectives is increasingly appreciated in clinical practic...

Predicting Individual Treatment Effects to Determine Duration of Dual Antiplatelet Therapy After Stent Implantation.

BACKGROUND: After coronary stent implantation, prolonged dual antiplatelet therapy (DAPT) increases ...

A machine learning-based Coagulation Risk Index predicts acute traumatic coagulopathy in bleeding trauma patients.

BACKGROUND: Acute traumatic coagulopathy (ATC) is a well-described phenomenon known to begin shortly...

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