Gastroenterology

Generalizable Pancreas Segmentation via a Dual Self-Supervised Learning Framework

Recently, numerous pancreas segmentation methods have achieved promising performance on local single-source datasets. However, these methods don't adequately account for generalizability issues, and hence typically show limited performance and low stability on test data from other sources. Considering the limited availability of distinct data sources, we seek to improve the generalization perfor...

Two-Stage Automatic Liver Classification System Based on Deep Learning Approach Using CT Images.

Alveolar echinococcosis (AE) is a parasitic disease caused by Echinococcus multilocularis, where early detection is crucial for effective treatment. This study introduces a novel method for the early diagnosis of liver diseases by differentiating between tumor, AE, and healthy cases using non-contrast CT images, which are widely accessible and eliminate the risks associated with contrast agents. T...

Effect of Deep Learning-Based Image Reconstruction on Lesion Conspicuity of Liver Metastases in Pre- and Post-contrast Enhanced Computed Tomography.

The purpose of this study was to investigate the utility of deep learning image reconstruction at medium and high intensity levels (DLIR-M and DLIR-H,...

Deep learning diagnosis of hepatic echinococcosis based on dual-modality plain CT and ultrasound images: a large-scale, multicenter, diagnostic study.

BACKGROUND: Given the current limited accuracy of imaging screening for Hepatic Echinococcosis (HCE) in under-resourced areas, the authors developed a...

Developing a Machine-Learning Prediction Model for Infliximab Response in Crohn's Disease: Integrating Clinical Characteristics and Longitudinal Laboratory Trends.

BACKGROUND: Achieving long-term clinical remission in Crohn's disease (CD) with antitumor necrosis factor α (anti-TNF-α) agents remains challenging.

Dietary Carrageenan Amplifies the Inflammatory Profile, but not Permeability, of Intestinal Epithelial Cells from Patients With Crohn's Disease.

BACKGROUND: The consumption of ultra-processed foods has increased significantly worldwide and is associated with the rise in inflammatory bowel disea...

A machine learning-based prediction model for colorectal liver metastasis.

Colorectal liver metastasis (CRLM) is a primary factor contributing to poor prognosis and metastasis in colorectal cancer (CRC) patients. This study a...

Identification of novel potential biomarkers using bulk RNA and single cells to build a neural network model for diagnosis of liver cancer.

BACKGROUND: As a common cancer, liver cancer imposes an unacceptable burden on patients, but its underlying molecular mechanisms are still not fully u...

Artificial intelligence-assisted diagnosis of early allograft dysfunction based on ultrasound image and data.

Early allograft dysfunction (EAD) significantly affects liver transplantation prognosis. This study evaluated the effectiveness of artificial intellig...

Enhancing noninvasive pancreatic cystic neoplasm diagnosis with multimodal machine learning.

Pancreatic cystic neoplasms (PCNs) are a complex group of lesions with a spectrum of malignancy. Accurate differentiation of PCN types is crucial for ...

Machine learning predicts prognosis in patients with gastroenteropancreatic neuroendocrine tumors with liver metastases.

BACKGROUND: Patients with gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) and liver metastases typically exhibit poor prognoses. However, a...

Hallucination-Aware Multimodal Benchmark for Gastrointestinal Image Analysis with Large Vision-Language Models

Vision-Language Models (VLMs) are becoming increasingly popular in the medical domain, bridging the gap between medical images and clinical language...

Enhancing segmentation accuracy of the common iliac vein in OLIF51 surgery in intraoperative endoscopic video through gamma correction: a deep learning approach.

PURPOSE: The principal objective of this study was to develop and evaluate a deep learning model for segmenting the common iliac vein (CIV) from intra...

A novel scheme for non-invasive drug delivery with a magnetically controlled drug delivering capsule endoscope.

There is a lack of effective means for precise drug delivery of gastrointestinal diseases. Herein we report a novel magnetically controlled drug deliv...

The Accuracy of ChatGPT-4o in Interpreting Chest and Abdominal X-Ray Images.

Large language models (LLMs), such as ChatGPT, have emerged as potential clinical support tools to enhance precision in personalized patient care, bu...

A novel framework for esophageal cancer grading: combining CT imaging, radiomics, reproducibility, and deep learning insights.

OBJECTIVE: This study aims to create a reliable framework for grading esophageal cancer. The framework combines feature extraction, deep learning with...

Unsupervised machine learning-based stratification and immune deconvolution of liver hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is the most prevalent type of liver cancer and a leading cause of cancer-related deaths globally. The tumou...

Emerging biomarkers for pancreatic cancer: from early detection to personalized therapy.

Pancreatic cancer (PC) remains one of the most lethal malignancies, primarily due to its poor prognosis and late diagnosis. Biomarkers are essential i...

Query-driven Document-level Scientific Evidence Extraction from Biomedical Studies

Extracting scientific evidence from biomedical studies for clinical research questions (e.g., Does stem cell transplantation improve quality of life...

Artificial intelligence in colorectal cancer liver metastases: From classification to precision medicine.

Colorectal cancer liver metastasis (CRLM) remains the leading cause of mortality among colorectal cancer (CRC) patients, with more than half eventuall...