Gastroenterology

GERD

Latest AI and machine learning research in gerd for healthcare professionals.

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Improved prediction of protein-protein interactions by a modified strategy using three conventional docking software in combination.

Proteins play a crucial role in many biological processes, where their interaction with other protei...

Artificial intelligence in digestive endoscopy: recent advances.

PURPOSE OF REVIEW: With the incessant advances in information technology and its implications in all...

Systematical analysis of underlying markers associated with Marfan syndrome via integrated bioinformatics and machine learning strategies.

Marfan syndrome (MFS) is a hereditary disease with high mortality. This study aimed to explore perip...

Single-Port Robotic Removal of a Submucosal Foreign Body in the Distal Hypopharynx.

In this report, we present a 55-year-old female with cervical stenosis that underwent C5-C7 anterior...

Deep learning-based prediction model for diagnosing gastrointestinal diseases using endoscopy images.

BACKGROUND: Gastrointestinal (GI) infections are quite common today around the world. Colonoscopy or...

Assisted documentation as a new focus for artificial intelligence in endoscopy: the precedent of reliable withdrawal time and image reporting.

BACKGROUND : Reliable documentation is essential for maintaining quality standards in endoscopy; how...

Recent Advances in Deep Learning for Protein-Protein Interaction Analysis: A Comprehensive Review.

Deep learning, a potent branch of artificial intelligence, is steadily leaving its transformative im...

Deep Learning Segmentation of the Right Ventricle in Cardiac MRI: The M&Ms Challenge.

In recent years, several deep learning models have been proposed to accurately quantify and diagnose...

Emerging Pharmacotherapeutic Strategies to Overcome Undruggable Proteins in Cancer.

Targeted therapies in cancer treatment can improve efficacy and reduce adverse effects by altering ...

Geometric graph neural networks on multi-omics data to predict cancer survival outcomes.

The advance of sequencing technologies has enabled a thorough molecular characterization of the geno...

Sequence-based machine learning method for predicting the effects of phosphorylation on protein-protein interactions.

Protein phosphorylation, catalyzed by kinases, is an important biochemical process, which plays an e...

Protein-Protein Interaction Sites Prediction Using Batch Normalization Based CNNs and Oversampling Method Borderline-SMOTE.

The recognition of protein-protein interaction sites (PPIs) is beneficial for the interpretation of ...

Applying deep learning to iterative screening of medium-sized molecules for protein-protein interaction-targeted drug discovery.

We combined a library of medium-sized molecules with iterative screening using multiple machine lear...

Using a stacked ensemble learning framework to predict modulators of protein-protein interactions.

Identifying small molecule protein-protein interaction modulators (PPIMs) is a highly promising and ...

Automated diagnosis of cardiovascular diseases from cardiac magnetic resonance imaging using deep learning models: A review.

In recent years, cardiovascular diseases (CVDs) have become one of the leading causes of mortality g...

Targeting Protein-Protein Interfaces with Peptides: The Contribution of Chemical Combinatorial Peptide Library Approaches.

Protein-protein interfaces play fundamental roles in the molecular mechanisms underlying pathophysio...

Design of a Convolutional Neural Network as a Deep Learning Tool for the Automatic Classification of Small-Bowel Cleansing in Capsule Endoscopy.

: Capsule endoscopy (CE) is a non-invasive method to inspect the small bowel that, like other entero...

Machine Learning Predicts the Oxidative Stress Subtypes Provide an Innovative Insight into Colorectal Cancer.

So far, it has been reached the academic consensus that the molecular subtypes are via genomic heter...

Deep learning on graphs for multi-omics classification of COPD.

Network approaches have successfully been used to help reveal complex mechanisms of diseases includi...

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