Gastroenterology

GERD

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

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Enhanced Feature-based Image Stitching for Endoscopic Videos in Pediatric Eosinophilic Esophagitis

Video endoscopy represents a major advance in the investigation of gastrointestinal diseases. Revi...

Expanding Training Data for Endoscopic Phenotyping of Eosinophilic Esophagitis

Eosinophilic esophagitis (EoE) is a chronic esophageal disorder marked by eosinophil-dominated inf...

Influence of color correction on pathology detection in Capsule Endoscopy

Pathology detection in Wireless Capsule Endoscopy (WCE) using deep learning has been explored in t...

EndoDINO: A Foundation Model for GI Endoscopy

In this work, we present EndoDINO, a foundation model for GI endoscopy tasks that achieves strong ...

Proteomic Learning of Gamma-Aminobutyric Acid (GABA) Receptor-Mediated Anesthesia

Anesthetics are crucial in surgical procedures and therapeutic interventions, but they come with s...

XL-Ranker: A Computational Workflow for Prioritizing Protein-Protein Interactions from Cross-Linking Mass Spectrometry Data

Protein-protein interactions (PPIs) are central to virtually all biological processes, and their dis...

ProtLoc-GRPO: Cell line-specific subcellular localization prediction using a graph-based model and reinforcement learning

Subcellular localization prediction is crucial for understanding protein functions and cellular proc...

GeoGAT-site: A Face-Centered Geometric Graph Attention Network for Protein-Protein Interface Prediction

Protein-protein interactions (PPIs) underpin the intricate machinery of cellular life, orchestrating...

ProteomeLM: A proteome-scale language model allowing fast prediction of protein-protein interactions and gene essentiality across taxa

Language models starting from biological sequence data are advancing many inference problems, both a...

HPInet: Interpretable prediction of Host-Pathogen protein-protein Interactions using a transformer-based neural network

Gram-negative bacteria utilize a series of secretion systems (T1SS-T10SS) to deliver secreted effect...

C3PI: Component Puzzle Protein-Protein Interaction Prediction

Proteins primarily perform their functions through interactions with other proteins, making the accu...

Improving Protein Interaction Prediction in GenPPi: A Novel Interaction Sampling Approach Preserving Network Topology

Computational prediction of protein-protein interactions (PPIs) is crucial for understanding cell bi...

In Silico Design of APOE ɛ4 Interaction Inhibitor Peptides for Alzheimer’s Disease

Protein-protein interactions (PPIs) are essential for cellular functions, and their aberrant formati...

Instruction-tuned extraction of virus-host interactions from integrated scientific evidence

Viral infectious diseases continue to pose a major threat to global health. Understanding protein-pr...

Protein-protein interaction priors shape biologically coherent latent spaces for causally concordant cross-omic translation

Deep learning models routinely compress omics into low-dimensional codes, yet many equally accurate ...

Multiplex mapping of protein-protein interaction interfaces

We describe peptide mapping through Split Antibiotic Resistance Complementation (SpARC-map), a metho...

GREmLN: A Cellular Graph Structure Aware Transcriptomics Foundation Model

The ever-increasing availability of large-scale single-cell profiles presents an opportunity to deve...

Protein Language Models are Accidental Taxonomists

Protein-protein interactions (PPIs) are fundamental to nearly all biological processes, yet their ex...

Discovery of molecular glues by modeling ternary complex conformational ensembles and thermodynamic stability

The rational design of molecular glue degraders is challenging because glue-mediated protein degrada...

Systematic discovery of single-cell protein networks in cancer with Shusi

Context-specific protein-protein interaction (PPI) drive heterogeneity of primary tumor, forming a f...

Language may be all omics needs: Harmonizing multimodal data for omics understanding with CellHermes

Decoding cellular systems requires integrating diverse omics data, yet most models are trained from ...

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