Latest AI and machine learning research in gastroenterology for healthcare professionals.
Pharmacokinetic data are not generally available for evaluating the toxicological potential of food chemicals. A simplified physiologically based pharmacokinetic (PBPK) model has been established to evaluate internal exposures to chemicals in rats or humans with no reference to in vitro or in vivo experimental data. In this study, reported liver toxicity levels in rats were extrapolated to humans ...
Identifying anatomical landmarks in endoscopic video frames is essential for the early diagnosis of gastrointestinal diseases. However, this task remains challenging due to variability in visual characteristics across different regions and the limited availability of annotated data. In this study, we propose a novel self-supervised learning (SSL) framework that integrates three complementary prete...
RATIONALE AND OBJECTIVES: Neoadjuvant chemotherapy (NAC) is a promising therapeutic strategy for managing locally advanced gastric cancer (LAGC), aimi...
Globally, chronic liver disease continues to be a major health concern that requires precise predictive models for prompt detection and treatment. U...
Hepatocellular carcinoma (HCC) is a prevalent cancer that significantly contributes to mortality globally, primarily due to its late diagnosis. Early ...
BACKGROUND: Radical gastrectomy with D2 lymphadenectomy is standard surgical protocol for locally advanced gastric cancer. The surgical experience and...
Hirschsprung's disease (HD) is a congenital birth defect diagnosed by identifying the lack of ganglion cells within the colon's muscularis propria, ...
Multimodal learning has been demonstrated to enhance performance across various clinical tasks, owing to the diverse perspectives offered by differe...
Hepatic vessels in computed tomography scans often suffer from image fragmentation and noise interference, making it difficult to maintain vessel in...
BACKGROUND: Wireless capsule endoscopy (WCE) has become an important noninvasive and portable tool for diagnosing digestive tract diseases and has bee...
The growing need for accurate and efficient 3D identification of tumors, particularly in liver segmentation, has spurred considerable research into ...
Background: Radiation pneumonitis is a side effect of thoracic radiation therapy. Recently, machine learning models with radiomic features have impr...
Objective: To develop a novel deep learning framework for the automated segmentation of colonic polyps in colonoscopy images, overcoming the limitat...
In image-guided liver surgery, the initial rigid alignment between preoperative and intraoperative data, often represented as point clouds, is cruci...
Informed by the success of the transformer model in various computer vision tasks, we design an end-to-end trainable model for the automatic detecti...
In order to seek a patient friendly and low-cost intestinal examination method, a structurally simple pneumatic soft intestinal robot inspired by inch...
Gastric tumors are neoplastic lesions that occur in the stomach, posing a great threat to human health. Gastric cancer represents the malignant form o...
Gastrointestinal (GI) bleeding is a serious medical condition that presents significant diagnostic challenges, particularly in settings with limited...
Lung and colon cancers are predominant contributors to cancer mortality. Early and accurate diagnosis is crucial for effective treatment. By utilizi...
Deep learning can predict depth maps and capsule ego-motion from capsule endoscopy videos, aiding in 3D scene reconstruction and lesion localization...