Peptic Ulcer Disease

Self-Supervised Lightweight Depth Estimation in Endoscopy Combining CNN and Transformer.

In recent years, an increasing number of medical engineering tasks, such as surgical navigation, pre-operative registration, and surgical robotics, rely on 3D reconstruction techniques. Self-supervised depth estimation has attracted interest in endoscopic scenarios because it does not require ground truth. Most existing methods depend on expanding the size of parameters to improve their performanc...

Identifying lncRNAs and mRNAs related to survival of NSCLC based on bioinformatic analysis and machine learning.

Non-small cell lung cancer (NSCLC) is the most common histopathological type, and it is purposeful for screening potential prognostic biomarkers for NSCLC. This study aims to identify the lncRNAs and mRNAs related to survival of non-small cell lung cancer (NSCLC). The expression profile data of lung adenocarcinoma and lung squamous cell carcinoma were downloaded in The Cancer Genome Atlas (TCGA) a...

Flexible Conformally Bioadhesive MXene Hydrogel Electronics for Machine Learning-Facilitated Human-Interactive Sensing.

Wearable epidermic electronics assembled from conductive hydrogels are attracting various research attention for their seamless integration with human...

UViT-Seg: An Efficient ViT and U-Net-Based Framework for Accurate Colorectal Polyp Segmentation in Colonoscopy and WCE Images.

Colorectal cancer (CRC) stands out as one of the most prevalent global cancers. The accurate localization of colorectal polyps in endoscopy images is ...

Using Machine Learning to Construct the Blood-Follicle Distribution Models of Various Trace Elements and Explore the Transport-Related Pathways with Multiomics Data.

Permeabilities of various trace elements (TEs) through the blood-follicle barrier (BFB) play an important role in oocyte development. However, it has ...

Construction of deep learning-based convolutional neural network model for automatic detection of fluid hysteroscopic endometrial micropolyps in infertile women with chronic endometritis.

OBJECTIVE(S): Chronic endometritis (CE) is a localized mucosal inflammatory disorder associated with female infertility of unknown etiology, endometri...

Artificial intelligence-assisted colonoscopy to identify histologic remission and predict the outcomes of patients with ulcerative colitis: A systematic review.

This systematic review evaluated the current status of AI-assisted colonoscopy to identify histologic remission and predict the clinical outcomes of p...

A deep-learning approach to predict bleeding risk over time in patients on extended anticoagulation therapy.

BACKGROUND: Thus far, all the clinical models developed to predict major bleeding in patients on extended anticoagulation therapy use the baseline pre...

Consensus statements on the current landscape of artificial intelligence applications in endoscopy, addressing roadblocks, and advancing artificial intelligence in gastroenterology.

BACKGROUND AND AIMS: The American Society for Gastrointestinal Endoscopy (ASGE) AI Task Force along with experts in endoscopy, technology space, regul...

Deep learning assists detection of esophageal cancer and precursor lesions in a prospective, randomized controlled study.

Endoscopy is the primary modality for detecting asymptomatic esophageal squamous cell carcinoma (ESCC) and precancerous lesions. Improving detection r...

A Swin transformer encoder-based StyleGAN for unbalanced endoscopic image enhancement.

With the rapid development of artificial intelligence, automated endoscopy-assisted diagnostic systems have become an effective tool for reducing the ...

Cascade-EC Network: Recognition of Gastrointestinal Multiple Lesions Based on EfficientNet and CA_stm_Retinanet.

Capsule endoscopy (CE) is non-invasive and painless during gastrointestinal examination. However, capsule endoscopy can increase the workload of image...

Therapeutic endoscopy: Recent updates and future directions.

The landscape of therapeutic endoscopy has undergone a remarkable evolution over the past few decades, carving out a niche that merges innovative tech...

SurfPro-NN: A 3D point cloud neural network for the scoring of protein-protein docking models based on surfaces features and protein language models.

Protein-protein interactions (PPI) play a crucial role in numerous key biological processes, and the structure of protein complexes provides valuable ...

Automated detection of small bowel lesions based on capsule endoscopy using deep learning algorithm.

BACKGROUND: In order to overcome the challenges of lesion detection in capsule endoscopy (CE), we improved the YOLOv5-based deep learning algorithm an...

EndoViT: pretraining vision transformers on a large collection of endoscopic images.

PURPOSE: Automated endoscopy video analysis is essential for assisting surgeons during medical procedures, but it faces challenges due to complex surg...

Artificial Intelligence and Medical Liability in Gastrointestinal Endoscopy.

Deep learning-based quantification of total bleeding volume and its association with complications, disability, and death in patients with aneurysmal subarachnoid hemorrhage.

OBJECTIVE: The relationships between immediate bleeding severity, postoperative complications, and long-term functional outcomes in patients with aneu...

Robustness evaluation of deep neural networks for endoscopic image analysis: Insights and strategies.

Computer-aided detection and diagnosis systems (CADe/CADx) in endoscopy are commonly trained using high-quality imagery, which is not representative f...

Photocatalytic decomposition of metronidazole by zinc hexaferrite coated with bismuth oxyiodide magnetic nanocomposite: Advanced modelling and optimization with artificial neural network.

The objective of the present study was to employ a green synthesis method to produce a sustainable ZnFeO/BiOI nanocomposite and evaluate its efficacy ...