Latest AI and machine learning research in gerd for healthcare professionals.
Due to their high versatility in tasks such as image captioning, document analysis, and automated content generation, multimodal Large Language Models (LLMs) have attracted significant attention across various industrial fields. In particular, they have been shown to surpass specialized models in Optical Character Recognition (OCR). Nevertheless, their performance under different image condition...
The clinical application of binocular endoscope relies primarily on the visual system of physicians to create a three-dimensional effect, but it cannot provide accurate depth information. The utilization of 3D reconstruction technology in binocular endoscopy can facilitate the recovery of image depth information, and the application of deep learning-based 3D reconstruction technology can significa...
Motivation: In recent years, protein function prediction has broken through the bottleneck of sequence features, significantly improving prediction ...
The integration of heterogeneous multi-omics datasets at a systems level remains a central challenge for developing analytical and computational mod...
Multi-map Sparse Monocular visual Simultaneous Localization and Mapping applied to monocular endoscopic sequences has proven efficient to robustly r...
This article discusses the manuscript recently published in the , which explores the application of deep learning models in decision-making processes ...
Background: Predicting the efficacy of combination therapies is a critical challenge in clinical decision-making, particularly for diseases requirin...
Protein-protein interaction (PPI) prediction is an instrumental means in elucidating the mechanisms underlying cellular operations, holding signific...
Endoscopy serves as an essential procedure for evaluating the gastrointestinal (GI) tract and plays a pivotal role in identifying GI-related disorde...
Real-time acquisition of accurate depth of scene is essential for automated robotic minimally invasive surgery, and stereo matching with binocular e...
Zero-shot medical detection can further improve detection performance without relying on annotated medical images even upon the fine-tuned model, sh...
Due to the sensitive nature of personally identifiable information (PII), its owners may have the authority to control its inclusion or request its ...
The role of ketone bodies in Alzheimers disease (AD) remains incompletely understood, particularly regarding their influence on amyloid pathology. W...
Referring Medical Image Sequence Segmentation (Ref-MISS) is a novel and challenging task that aims to segment anatomical structures in medical image...
BACKGROUND: Borrmann type-4 (B-4) advanced gastric cancer is challenging to diagnose through routine endoscopy, leading to a poor prognosis. The objec...
The bicuspid aortic valve (BAV) is the most prevalent congenital heart defect and may require surgery for complications such as stenosis, regurgitat...
Identification of protein-protein interactions (PPIs) helps derive cellular mechanistic understanding, particularly in the context of complex condit...
Video endoscopy represents a major advance in the investigation of gastrointestinal diseases. Reviewing endoscopy videos often involves frequent adj...
Eosinophilic esophagitis (EoE) is a chronic esophageal disorder marked by eosinophil-dominated inflammation. Diagnosing EoE usually involves endosco...
Pathology detection in Wireless Capsule Endoscopy (WCE) using deep learning has been explored in the recent past. However, deep learning models can ...