GERD

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*-based deep feature engineering model with endoscopy images. The novelty of this work is the development of ResNet50*, a new variant of the ResNet model, featuring convolution-based residual blocks and a pooling-based attention mechanism similar to P...

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 bowel (SB) capsule endoscopy (CE), including vascular abnormalities with high (P2), intermediate (P1) or low (P0) bleeding potential, while dramatically decreasing the reading time. We aimed to improve the performance of a DL algorithm by characteriz...

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...

Comprehensive review of dysphagia and technological advances in dysphagia food.

As the global population ages, dysphagia is becoming increasingly common among the elderly, posing serious risks such as choking, aspiration pneumonia...

Machine Learning Identifies Clinically Distinct Phenotypes in Patients With Aortic Regurgitation.

BACKGROUND: Aortic regurgitation (AR) is a prevalent valve disease with a long latent period before symptoms appear. Recent data has suggested the rol...

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 ...

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...

Enhancing image-based diagnosis of gastrointestinal tract diseases through deep learning with EfficientNet and advanced data augmentation techniques.

The early detection and diagnosis of gastrointestinal tract diseases, such as ulcerative colitis, polyps, and esophagitis, are crucial for timely trea...

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,...

A deep learning-based method for assessing tricuspid regurgitation using continuous wave Doppler spectra.

Transthoracic echocardiography (TTE) is widely recognized as one of the principal modalities for diagnosing tricuspid regurgitation (TR). The diagnost...

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...

Synergistic biophysics and machine learning modeling to rapidly predict cardiac growth probability.

Computational models that can predict growth and remodeling of the heart could have important clinical applications. However, the time it takes to cal...

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...

The role of aspirin in preventing gastrointestinal cancers.

Cancer remains an increasing global health issue and is projected to cause 50% of all global deaths by 2050. Gastrointestinal (GI) tract cancers curre...

Past, Present, and Future: A History Lesson in Artificial Intelligence.

Over the past 5 decades, artificial intelligence (AI) has evolved rapidly. Moving from basic models to advanced machine learning and deep learning sys...

Plasma protein-based identification of neuroimage-driven subtypes in mild cognitive impairment via protein-protein interaction aware explainable graph propagational network.

As an early indicator of dementia, mild cognitive impairment (MCI) requires specialized treatment according to its subtypes for the effective preventi...