Gastroenterology

Machine learning liver-injuring drug interactions with non-steroidal anti-inflammatory drugs (NSAIDs) from a retrospective electronic health record (EHR) cohort.

Drug-drug interactions account for up to 30% of adverse drug reactions. Increasing prevalence of electronic health records (EHRs) offers a unique opportunity to build machine learning algorithms to identify drug-drug interactions that drive adverse events. In this study, we investigated hospitalizations' data to study drug interactions with non-steroidal anti-inflammatory drugs (NSAIDS) that resul...

3D Deep Learning Model for the Pretreatment Evaluation of Treatment Response in Esophageal Carcinoma: A Prospective Study (ChiCTR2000039279).

PURPOSE: To develop and validate a pretreatment computed tomography (CT)-based deep-learning (DL) model for predicting the treatment response to concurrent chemoradiation therapy (CCRT) among patients with locally advanced thoracic esophageal squamous cell carcinoma (TESCC).

Reducing adenoma miss rate of colonoscopy assisted by artificial intelligence: a multicenter randomized controlled trial.

BACKGROUND: We have developed the computer-aided detection (CADe) system using an original deep learning algorithm based on a convolutional neural net...

Multiclassification of Endoscopic Colonoscopy Images Based on Deep Transfer Learning.

With the continuous improvement of human living standards, dietary habits are constantly changing, which brings various bowel problems. Among them, th...

Esophagus Segmentation in CT Images via Spatial Attention Network and STAPLE Algorithm.

One essential step in radiotherapy treatment planning is the organ at risk of segmentation in Computed Tomography (CT). Many recent studies have focus...

A Semiautomated Deep Learning Approach for Pancreas Segmentation.

Accurate pancreas segmentation from 3D CT volumes is important for pancreas diseases therapy. It is challenging to accurately delineate the pancreas d...

Multi-institutional development and external validation of machine learning-based models to predict relapse risk of pancreatic ductal adenocarcinoma after radical resection.

BACKGROUND: Surgical resection is the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC) and the survival of patients aft...

Move Over, Colon. It's Time for the Esophagus to Take Center Stage for Artificial Intelligence and Computer-Aided Detection of Barrett's!

The Immune Subtypes and Landscape of Gastric Cancer and to Predict Based on the Whole-Slide Images Using Deep Learning.

BACKGROUND: Gastric cancer (GC) is a highly heterogeneous tumor with different responses to immunotherapy. Identifying immune subtypes and landscape o...

A Commentary on "Long-term oncological outcomes in robotic versus laparoscopic approach for rectal cancer: A systematic review and meta-analysis" [Int. J. Surg. 80 (2020) 225-230].

Artificial intelligence for the detection of gastric precancerous conditions using image-enhanced endoscopy: What kind of abilities are required for application in real-world clinical practice?

A Machine Learning Approach Enables Quantitative Measurement of Liver Histology and Disease Monitoring in NASH.

BACKGROUND AND AIMS: Manual histological assessment is currently the accepted standard for diagnosing and monitoring disease progression in NASH, but ...

The dosimetric impact of deep learning-based auto-segmentation of organs at risk on nasopharyngeal and rectal cancer.

PURPOSE: To investigate the dosimetric impact of deep learning-based auto-segmentation of organs at risk (OARs) on nasopharyngeal and rectal cancer.

Initial experience with a suprapubic single-port robotic right hemicolectomy in patients with colon cancer.

BACKGROUND: We developed a novel suprapubic single-port robotic right hemicolectomy (spRHC) procedure for patients with right colon cancer using a da ...

Associating Preoperative MRI Features and Gene Expression Signatures of Early-stage Hepatocellular Carcinoma Patients using Machine Learning.

BACKGROUND AND AIMS: The relationship between quantitative magnetic resonance imaging (MRI) imaging features and gene-expression signatures associated...

Robotic resection for hydatid disease of the liver.

Robotic-assisted surgery for the management of hepatic echinococcosis was introduced in 2016. The advantage it offers over laparoscopy is less rigidit...

The clinical impact of robot-assisted laparoscopic rectal cancer surgery associated with robot-assisted radical prostatectomy.

INTRODUCTION: Robot-assisted laparoscopic surgery has been performed in various fields, especially in the pelvic cavity. However, little is known abou...

A Nomogram Based on a Collagen Feature Support Vector Machine for Predicting the Treatment Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer Patients.

BACKGROUND: The relationship between collagen features (CFs) in the tumor microenvironment and the treatment response to neoadjuvant chemoradiotherapy...

Analytical Modeling of the Interaction Between Soft Balloon-Like Actuators and Soft Tubular Environment for Gastrointestinal Inspection.

Accessing tubular environment is critical in medicine. For example, gastrointestinal tract related cancers are the leading causes of cancer deaths glo...

Endoscopic submucosal dissection using a detachable assistant robot: a comparative in vivo feasibility study (with video).

BACKGROUND: Appropriate tissue tension and clear visibility of the dissection area using traction are essential for effective and safe endoscopic subm...