Gastroenterology

Automated Quantification of HER2 Amplification Levels Using Deep Learning.

HER2 assessment is necessary for patient selection in anti-HER2 targeted treatment. However, manual ...

Semi-Supervised Detection Model Based on Adaptive Ensemble Learning for Medical Images.

Introducing deep learning technologies into the medical image processing field requires accuracy gua...

Effects of feeding of vitamin C on embryonic development, hatching process, and chick rectal temperature of broiler embryos.

Maternal nutritional status plays a crucial role in embryonic development and has persistent effects...

Editorial: Modelling esophageal adenocarcinoma.

Integrating single cell analysis and machine learning methods reveals stem cell-related gene S100A10 as an important target for prediction of liver cancer diagnosis and immunotherapy.

BACKGROUND: Hepatocellular carcinoma (LIHC) poses a significant health challenge worldwide, primaril...

Advances in the clinical application of machine learning in acute pancreatitis: a review.

Traditional disease prediction models and scoring systems for acute pancreatitis (AP) are often inad...

Plasma Epstein-Barr Virus DNA load for diagnostic and prognostic assessment in intestinal Epstein-Barr Virus infection.

BACKGROUND: The prospective application of plasma Epstein-Barr virus (EBV) DNA load as a noninvasive...

Isolation, identification and characteristics of from diseased rainbow trout ().

is an opportunistic pathogen that can infect humans, animals and aquatic species, which is widely d...

Deep learning-based prediction of HER2 status and trastuzumab treatment efficacy of gastric adenocarcinoma based on morphological features.

BACKGROUND: First-line treatment for advanced gastric adenocarcinoma (GAC) with human epidermal grow...

Evaluating the pathological and clinical implications of errors made by an artificial intelligence colon biopsy screening tool.

OBJECTIVE: Artificial intelligence (AI) tools for histological diagnosis offer great potential to he...

Predicting the risk of gastroparesis in critically ill patients after CME using an interpretable machine learning algorithm - a 10-year multicenter retrospective study.

BACKGROUND: Gastroparesis following complete mesocolic excision (CME) can precipitate a cascade of s...

Interaction of human gut microbiota and local immune system in progression of colorectal adenoma (MIMICA-1): a protocol for a prospective, observational cohort study.

INTRODUCTION: The current understanding of colorectal carcinogenesis is based on the adenoma-carcino...

A hybrid framework for colorectal cancer detection and U-Net segmentation using polynetDWTCADx.

"PolynetDWTCADx" is a sophisticated hybrid model that was developed to identify and distinguish colo...

Artificial Intelligence in Gastrointestinal Imaging: Advances and Applications.

While artificial intelligence (AI) has shown considerable progress in many areas of medical imaging,...

Prediction of real-time cine-MR images during MRI-guided radiotherapy of liver cancer using a GAN-ConvLSTM network.

BACKGROUND: Respiratory motion during radiotherapy (RT) may reduce the therapeutic effect and increa...

Automated ultrasonography of hepatocellular carcinoma using discrete wavelet transform based deep-learning neural network.

This study introduces HCC-Net, a novel wavelet-based approach for the accurate diagnosis of hepatoce...

mCNN-glucose: Identifying families of glucose transporters using a deep convolutional neural network based on multiple-scanning windows.

Glucose transporters are essential carrier proteins that function on the phospholipid bilayer to fac...

Integrating artificial intelligence with endoscopic ultrasound in the early detection of bilio-pancreatic lesions: Current advances and future prospects.

The integration of Artificial Intelligence (AI) in endoscopic ultrasound (EUS) represents a transfor...

Classification of Irritable Bowel Syndrome Using Brain Functional Connectivity Strength and Machine Learning.

BACKGROUND: Irritable Bowel Syndrome (IBS) is a prevalent condition characterized by dysregulated br...

Deep-Learning-Based Reconstruction of Single-Breath-Hold 3 mm HASTE Improves Abdominal Image Quality and Reduces Acquisition Time: A Quantitative Analysis.

Breath-hold T2-weighted half-Fourier acquisition single-shot turbo spin echo (HASTE) magnetic reson...

Machine learning based identification of an amino acid metabolism related signature for predicting prognosis and immune microenvironment in pancreatic cancer.

BACKGROUND: Pancreatic cancer is a highly aggressive neoplasm characterized by poor diagnosis. Amino...