Peptic Ulcer Disease

QUAIDE - Quality assessment of AI preclinical studies in diagnostic endoscopy.

Artificial intelligence (AI) holds significant potential for enhancing quality of gastrointestinal (GI) endoscopy, but the adoption of AI in clinical practice is hampered by the lack of rigorous standardisation and development methodology ensuring generalisability. The aim of the Quality Assessment of pre-clinical AI studies in Diagnostic Endoscopy (QUAIDE) Explanation and Checklist was to develop...

RGCNPPIS: A Residual Graph Convolutional Network for Protein-Protein Interaction Site Prediction.

Accurate identification of protein-protein interaction (PPI) sites is crucial for understanding the mechanisms of biological processes, developing PPI networks, and detecting protein functions. Currently, most computational methods primarily concentrate on sequence context features and rarely consider the spatial neighborhood features. To address this limitation, we propose a novel residual graph ...

An End-to-End Knowledge Graph Fused Graph Neural Network for Accurate Protein-Protein Interactions Prediction.

Protein-protein interactions (PPIs) are essential to understanding cellular mechanisms, signaling networks, disease processes, and drug development, a...

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 targeted therapies, reducing drug-related toxicities an...

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 algorithms for detecting protein-protein interactions...

Current Status and Future Directions of Research on Artificial Intelligence in Nasopharyngolaryngoscopy.

BACKGROUND: The nasopharyngolaryngoscopy (NPL) has emerged as a valuable tool for detecting early cases of head and neck cancers. However, misdiagnose...

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 various gastrointestinal diseases using a new ResNet50*...

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 performance for the detection of vascular lesions via small ...

Application of artificial intelligence in laryngeal lesions: a systematic review and meta-analysis.

OBJECTIVE: The objective of this systematic review and meta-analysis was to evaluate the diagnostic accuracy of AI-assisted technologies, including en...

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 this issue has yet to be conclusively resolved. The...

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 mechanisms, contributing significantly to advances ...

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

BACKGROUND: Intraoperative hemorrhage during laparoscopic hepatectomy (LH) is a risk factor for negative postoperative outcomes. Ensuring appropriate ...

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 various biomedical applications. Computational methods f...

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, including the binding of antibodies to antigens,...

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 interactions, known as protein-protein interactio...

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-protein interaction (PPI) complexes, such as bindi...

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 Alzheimer's disease (AD) facilitates the identification ...

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, the need to process a vast number of images imposes...

MCI Net: Mamba- Convolutional lightweight self-attention medical image segmentation network.

With the development of deep learning in the field of medical image segmentation, various network segmentation models have been developed. Currently, ...

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-infection, identifying candidate hub genes and potential d...