Gastroenterology

Performance and clinical applicability of machine learning in liver computed tomography imaging: a systematic review.

OBJECTIVES: Machine learning (ML) for medical imaging is emerging for several organs and image modalities. Our objectives were to provide clinicians with an overview of this field by answering the following questions: (1) How is ML applied in liver computed tomography (CT) imaging? (2) How well do ML systems perform in liver CT imaging? (3) What are the clinical applications of ML in liver CT imag...

Screening of normal endoscopic large bowel biopsies with interpretable graph learning: a retrospective study.

OBJECTIVE: To develop an interpretable artificial intelligence algorithm to rule out normal large bowel endoscopic biopsies, saving pathologist resources and helping with early diagnosis.

Deep learning-based classification of organs at risk and delineation guideline in pelvic cancer radiation therapy.

Deep learning (DL) models for radiation therapy (RT) image segmentation require accurately annotated training data. Multiple organ delineation guideli...

Major hepatectomy in elderly patients: possible benefit from robotic platform utilization.

INTRODUCTION: Robotic surgery has been increasingly utilized, yet its application for hepato-pancreato-biliary (HPB) procedures remains low due to tec...

Robotic posterior pelvic exenteration for a huge rectal gastrointestinal stromal tumour - A video vignette.

Predicting the survival of patients with pancreatic neuroendocrine neoplasms using deep learning: A study based on Surveillance, Epidemiology, and End Results database.

BACKGROUND: The study aims to evaluate the performance of three advanced machine learning algorithms and a traditional Cox proportional hazard (CoxPH)...

ChatGPT in Colorectal Surgery: A Promising Tool or a Passing Fad?

Colorectal surgery is a specialized branch of surgery that involves the diagnosis and treatment of conditions affecting the colon, rectum, and anus. I...

Robot-assisted low anterior resection for a rectal cancer patient with ileal conduit: A case report.

Surgery for rectal cancer patients with an ileal conduit after total cystectomy is difficult because adhesions in the pelvis and around the ileal cond...

A trial deep learning-based model for four-class histologic classification of colonic tumor from narrow band imaging.

Narrow band imaging (NBI) has been extensively utilized as a diagnostic tool for colorectal neoplastic lesions. This study aimed to develop a trial de...

Chronic Stress Exposure Alters the Gut Barrier: Sex-Specific Effects on Microbiota and Jejunum Tight Junctions.

BACKGROUND: Major depressive disorder (MDD) is the leading cause of disability worldwide. Of individuals with MDD, 30% to 50% are unresponsive to comm...

A novel staging system based on deep learning for overall survival in patients with esophageal squamous cell carcinoma.

PURPOSE: We developed DeepSurv, a deep learning approach for predicting overall survival (OS) in patients with esophageal squamous cell carcinoma (ESC...

Machine and deep learning in inflammatory bowel disease.

PURPOSE OF REVIEW: The Management of inflammatory bowel disease (IBD) has evolved with the introduction and widespread adoption of biologic agents; ho...

An Investigation about Modern Deep Learning Strategies for Colon Carcinoma Grading.

Developing computer-aided approaches for cancer diagnosis and grading is currently receiving an increasing demand: this could take over intra- and int...

A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories.

Pancreatic cancer is an aggressive disease that typically presents late with poor outcomes, indicating a pronounced need for early detection. In this ...

Robotic instruments outside the surgical field can cause problems: A case of critical bleeding during robotic distal pancreatectomy.

Robotic surgery has technical advantages including high optical magnification and articulation of forceps. However, the surgical field tends to be nar...

Deep learning based synthetic CT from cone beam CT generation for abdominal paediatric radiotherapy.

. Adaptive radiotherapy workflows require images with the quality of computed tomography (CT) for re-calculation and re-optimisation of radiation dose...

18F-FDG PET/CT Image Deep Learning Predicts Colon Cancer Survival.

Colon cancer is a type of cancer that begins in the large intestine. In the process of efficacy evaluation, postoperative recurrence prediction and me...

[Robotics in Liver Surgery - Tips and Tricks].

Since minimally invasive liver surgery has proven benefits over open surgery, this technique should also be implemented more broadly in Germany. With ...

Four-Dimensional Cone Beam CT Imaging Using a Single Routine Scan via Deep Learning.

A novel method is proposed to obtain four-dimensional (4D) cone-beam computed tomography (CBCT) images from a routine scan in patients with upper abdo...

Deep learning techniques in liver tumour diagnosis using CT and MR imaging - A systematic review.

Deep learning has become a thriving force in the computer aided diagnosis of liver cancer, as it solves extremely complicated challenges with high acc...