Peptic Ulcer Disease

Sim2Real in endoscopy segmentation with a novel structure aware image translation

Automatic segmentation of anatomical landmarks in endoscopic images can provide assistance to doctors and surgeons for diagnosis, treatments or medical training. However, obtaining the annotations required to train commonly used supervised learning methods is a tedious and difficult task, in particular for real images. While ground truth annotations are easier to obtain for synthetic data, model...

Multimodal Graph Representation Learning for Robust Surgical Workflow Recognition with Adversarial Feature Disentanglement

Surgical workflow recognition is vital for automating tasks, supporting decision-making, and training novice surgeons, ultimately improving patient safety and standardizing procedures. However, data corruption can lead to performance degradation due to issues like occlusion from bleeding or smoke in surgical scenes and problems with data storage and transmission. In this case, we explore a robus...

The influence of prompt engineering on large language models for protein-protein interaction identification in biomedical literature.

Identifying protein-protein interactions (PPIs) is a foundational task in biomedical natural language processing. While specialized models have been d...

A Comprehensive Review of Arachnoid Cysts.

Arachnoid cysts are cerebrospinal fluid (CSF)-filled sacs that develop within the arachnoid membrane surrounding the brain or spinal cord, often remai...

WEO Newsletter: The Impact of Artificial Intelligence on Gastrointestinal Endoscopy.

eNCApsulate: NCA for Precision Diagnosis on Capsule Endoscopes

Wireless Capsule Endoscopy is a non-invasive imaging method for the entire gastrointestinal tract, and is a pain-free alternative to traditional end...

Systematic Hardware Integration Testing for Smart Video-based Medical Device Prototypes

This paper presents a hardware-in-the-loop (HIL) verification system for intelligent, camera-based in-body medical devices. A case study of a Video ...

PPS-Ctrl: Controllable Sim-to-Real Translation for Colonoscopy Depth Estimation

Accurate depth estimation enhances endoscopy navigation and diagnostics, but obtaining ground-truth depth in clinical settings is challenging. Synth...

Feature Mixing Approach for Detecting Intraoperative Adverse Events in Laparoscopic Roux-en-Y Gastric Bypass Surgery

Intraoperative adverse events (IAEs), such as bleeding or thermal injury, can lead to severe postoperative complications if undetected. However, the...

Enhanced Anomaly Detection for Capsule Endoscopy Using Ensemble Learning Strategies

Capsule endoscopy is a method to capture images of the gastrointestinal tract and screen for diseases which might remain hidden if investigated with...

Noninvasive prediction of esophagogastric varices in hepatitis B: An extreme gradient boosting model based on ultrasound and serology.

BACKGROUND: Severe esophagogastric varices (EGVs) significantly affect prognosis of patients with hepatitis B because of the risk of life-threatening ...

Artificial intelligence-aided optical biopsy improves the diagnosis of esophageal squamous neoplasm.

BACKGROUND: Early detection of esophageal squamous neoplasms (ESN) is essential for improving patient prognosis. Optical diagnosis of ESN remains chal...

Artificial intelligence in bronchoscopy: a systematic review.

BACKGROUND: Artificial intelligence (AI) systems have been implemented to improve the diagnostic yield and operators' skills within endoscopy. Similar...

Multi-Task Learning for Extracting Menstrual Characteristics from Clinical Notes

Menstrual health is a critical yet often overlooked aspect of women's healthcare. Despite its clinical relevance, detailed data on menstrual charact...

Context-Independent OCR with Multimodal LLMs: Effects of Image Resolution and Visual Complexity

Due to their high versatility in tasks such as image captioning, document analysis, and automated content generation, multimodal Large Language Mode...

[Three-Dimensional Reconstruction Technique and Its Application of Binocular Endoscopic Images Based on Deep Learning].

The clinical application of binocular endoscope relies primarily on the visual system of physicians to create a three-dimensional effect, but it canno...

MSNGO: multi-species protein function annotation based on 3D protein structure and network propagation

Motivation: In recent years, protein function prediction has broken through the bottleneck of sequence features, significantly improving prediction ...

Graph Kolmogorov-Arnold Networks for Multi-Cancer Classification and Biomarker Identification, An Interpretable Multi-Omics Approach

The integration of heterogeneous multi-omics datasets at a systems level remains a central challenge for developing analytical and computational mod...

3D Convolutional Neural Networks for Improved Detection of Intracranial bleeding in CT Imaging

Background: Intracranial bleeding (IB) is a life-threatening condition caused by traumatic brain injuries, including epidural, subdural, subarachnoi...

3D Densification for Multi-Map Monocular VSLAM in Endoscopy

Multi-map Sparse Monocular visual Simultaneous Localization and Mapping applied to monocular endoscopic sequences has proven efficient to robustly r...