Gastroenterology

A deep learning-based model improves diagnosis of early gastric cancer under narrow band imaging endoscopy.

BACKGROUND: Diagnosis of early gastric cancer (EGC) under narrow band imaging endoscopy (NBI) is dependent on expertise and skills. We aimed to elucidate whether artificial intelligence (AI) could diagnose EGC under NBI and evaluate the diagnostic assistance of the AI system.

Epidural anesthesia needle guidance by forward-view endoscopic optical coherence tomography and deep learning.

Epidural anesthesia requires injection of anesthetic into the epidural space in the spine. Accurate placement of the epidural needle is a major challenge. To address this, we developed a forward-view endoscopic optical coherence tomography (OCT) system for real-time imaging of the tissue in front of the needle tip during the puncture. We tested this OCT system in porcine backbones and developed a ...

Hyperspectral Image Analysis of Colon Tissue and Deep Learning for Characterization of Health care.

Colon cancer is a disease characterized by the unusual and uncontrolled development of cells that are found in the large intestine. If the tumour exte...

Deep learning techniques for liver and liver tumor segmentation: A review.

Liver and liver tumor segmentation from 3D volumetric images has been an active research area in the medical image processing domain for the last few ...

Intuitive endoscopic robot master device with image orientation correction.

BACKGROUND: The camera of an endoscope is fixed to the device, and the image rotates together with the endoscope. This can lead to visual confusion fo...

Trivariate Linear Regression and Machine Learning Prediction of Possible Roles of Efflux Transporters in Estimated Intestinal Permeability Values of 301 Disparate Chemicals.

A system for predicting apparent bidirectional permeability (P) across Caco-2 cells of diverse chemicals has been reported. The present study aimed to...

Hybrid and Deep Learning Approach for Early Diagnosis of Lower Gastrointestinal Diseases.

Every year, nearly two million people die as a result of gastrointestinal (GI) disorders. Lower gastrointestinal tract tumors are one of the leading c...

Intestinal fibrosis classification in patients with Crohn's disease using CT enterography-based deep learning: comparisons with radiomics and radiologists.

OBJECTIVES: Accurate evaluation of bowel fibrosis in patients with Crohn's disease (CD) remains challenging. Computed tomography enterography (CTE)-ba...

Robotic left hemicolectomy with intracorporeal anastomosis: Description of the technique and initial results.

AIM: The aim was to describe the robot-assisted intracorporeal anastomosis technique in left colon surgery (rLCS) and report the initial results.

Diagnosis of Nonperitonealized Colorectal Cancer with Computerized Tomography Image Features under Deep Learning.

This study aimed to explore the value of abdominal computerized tomography (CT) three-dimensional reconstruction using the dense residual single-axis ...

Machine learning-based system for prediction of ascites grades in patients with liver cirrhosis using laboratory and clinical data: design and implementation study.

OBJECTIVES: The aim of the study was to implement a non-invasive model to predict ascites grades among patients with cirrhosis.

Computed Tomography Texture Features and Risk Factor Analysis of Postoperative Recurrence of Patients with Advanced Gastric Cancer after Radical Treatment under Artificial Intelligence Algorithm.

Computer tomography texture analysis (CTTA) based on the V-Net convolutional neural network (CNN) algorithm was used to analyze the recurrence of adva...

Metabonomic and transcriptomic analyses of glycosides tablet-induced hepatotoxicity in rats.

We aimed to explore novel biomarkers involved in alterations of metabolism and gene expression related to the hepatotoxic effects of glycosides table...

A prediction model for pathological findings after neoadjuvant chemoradiotherapy for resectable locally advanced esophageal squamous cell carcinoma based on endoscopic images using deep learning.

OBJECTIVES: To propose deep-learning (DL)-based predictive model for pathological complete response rate for resectable locally advanced esophageal sq...

Deep-Learning-Based Algorithm for the Removal of Electromagnetic Interference Noise in Photoacoustic Endoscopic Image Processing.

Despite all the expectations for photoacoustic endoscopy (PAE), there are still several technical issues that must be resolved before the technique ca...

A deep learning method to assist with chronic atrophic gastritis diagnosis using white light images.

BACKGROUND: Chronic atrophic gastritis is a common preneoplastic condition of the stomach with a low detection rate during endoscopy.

Deep learning on time series laboratory test results from electronic health records for early detection of pancreatic cancer.

The multi-modal and unstructured nature of observational data in Electronic Health Records (EHR) is currently a significant obstacle for the applicati...

A Deep Learning Model Based on MRI and Clinical Factors Facilitates Noninvasive Evaluation of KRAS Mutation in Rectal Cancer.

BACKGROUND: Recent studies showed the potential of MRI-based deep learning (DL) for assessing treatment response in rectal cancer, but the role of MRI...

A deep learning model and human-machine fusion for prediction of EBV-associated gastric cancer from histopathology.

Epstein-Barr virus-associated gastric cancer (EBVaGC) shows a robust response to immune checkpoint inhibitors. Therefore, a cost-efficient and accessi...

Calf Thymus Polypeptide Restrains the Growth of Colorectal Tumor Regulating the Intestinal Microbiota-Mediated Immune Function.

Calf thymus polypeptide (CTP), with a molecular mass of <10 kDa, is prepared from the thymus of less than 30-day-old newborn cattle. In the present st...