Gastroenterology

Deep learning to predict lymph node status on pre-operative staging CT in patients with colon cancer.

INTRODUCTION: Lymph node (LN) metastases are an important determinant of survival in patients with colon cancer, but remain difficult to accurately diagnose on preoperative imaging. This study aimed to develop and evaluate a deep learning model to predict LN status on preoperative staging CT.

Tele-robotic distal gastrectomy with lymph node dissection on a cadaver.

The purpose of this study is to evaluate the performance of tele-robotic distal gastrectomy (tele-RDG) with lymph node dissection (LND) using a novel Japanese-made surgical robot hinotori™ (Medicaroid, Kobe, Japan) in a cadaver with a presumptive gastric cancer. The Cadaveric Anatomy and Surgical Training Laboratory (CAST-Lab.) at Hokkaido University and Kushiro City General Hospital (KCGH) are co...

Deep learning driven de novo drug design based on gastric proton pump structures.

Existing drugs often suffer in their effectiveness due to detrimental side effects, low binding affinity or pharmacokinetic problems. This may be over...

Robot-assisted fluorescent sentinel lymph node identification in early-stage colon cancer.

BACKGROUND: Patients with cT1-2 colon cancer (CC) have a 10-20% risk of lymph node metastases. Sentinel lymph node identification (SLNi) could improve...

An Overview of Robotic Colorectal Surgery Adoption and Training in Brazil.

Robotic surgical systems have rapidly become integrated into colorectal surgery practice in recent years, particularly for rectal resections, where t...

Artificial Intelligence and liver: Opportunities and barriers.

Artificial Intelligence (AI) has recently been shown as an excellent tool for the study of the liver; however, many obstacles still have to be overcom...

Identification of Fast Progressors Among Patients With Nonalcoholic Steatohepatitis Using Machine Learning.

BACKGROUND AND AIMS: There is a high unmet need to develop noninvasive tools to identify nonalcoholic fatty liver disease/nonalcoholic steatohepatitis...

Automating Ground Truth Annotations for Gland Segmentation Through Immunohistochemistry.

Microscopic evaluation of glands in the colon is of utmost importance in the diagnosis of inflammatory bowel disease and cancer. When properly trained...

Deep learning-based iodine contrast-augmenting algorithm for low-contrast-dose liver CT to assess hypovascular hepatic metastasis.

PURPOSE: To investigate the image quality and diagnostic performance of low-contrast-dose liver CT using a deep learning-based iodine contrast-augment...

Liver dysfunction on admission worsens clinical manifestations and outcomes of coronavirus disease 2019.

BACKGROUND: Liver dysfunction was common in coronavirus disease 2019 (COVID-19), but its association with clinical features and poor prognosis has not...

Deep learning in negative small-bowel capsule endoscopy improves small-bowel lesion detection and diagnostic yield.

OBJECTIVES: Although several studies have shown the usefulness of artificial intelligence to identify abnormalities in small-bowel capsule endoscopy (...

The Fidelity of Artificial Intelligence to Multidisciplinary Tumor Board Recommendations for Patients with Gastric Cancer: A Retrospective Study.

PURPOSE: Due to significant growth in the volume of information produced by cancer research, staying abreast of recent developments has become a chall...

Real-time liver motion estimation via deep learning-based angle-agnostic X-ray imaging.

BACKGROUND: Real-time liver imaging is challenged by the short imaging time (within hundreds of milliseconds) to meet the temporal constraint posted b...

Comparison of Clinical Efficacy Between Da Vinci Robot-Assisted Ivor Lewis Esophagectomy and McKeown Esophagectomy for Middle and Lower Thoracic Esophageal Cancer: A Multicenter Propensity Score-Matched Study.

BACKGROUND: We compared the perioperative efficacy and safety of da Vinci robot-assisted Ivor Lewis esophagectomy and McKeown esophagectomy for middle...

Collagen fiber centerline tracking in fibrotic tissue via deep neural networks with variational autoencoder-based synthetic training data generation.

The role of fibrillar collagen in the tissue microenvironment is critical in disease contexts ranging from cancers to chronic inflammations, as eviden...

Deep learning trained on lymph node status predicts outcome from gastric cancer histopathology: a retrospective multicentric study.

AIM: Gastric cancer (GC) is a tumour entity with highly variant outcomes. Lymph node metastasis is a prognostically adverse biomarker. We hypothesised...

An interpretable deep learning framework for predicting liver metastases in postoperative colorectal cancer patients using natural language processing and clinical data integration.

BACKGROUND: The significance of liver metastasis (LM) in increasing the risk of death for postoperative colorectal cancer (CRC) patients necessitates ...

Application value of an artificial intelligence-based diagnosis and recognition system in gastroscopy training for graduate students in gastroenterology: a preliminary study.

OBJECTIVE: This study aimed to discuss the application value of an artificial intelligence-based diagnosis and recognition system (AIDRS) in the teach...

CIRCE: Web-Based Platform for the Prediction of Cannabinoid Receptor Ligands Using Explainable Machine Learning.

The endocannabinoid system, which includes cannabinoid receptor 1 and 2 subtypes (CBR and CBR, respectively), is responsible for the onset of various ...

IRv2-Net: A Deep Learning Framework for Enhanced Polyp Segmentation Performance Integrating InceptionResNetV2 and UNet Architecture with Test Time Augmentation Techniques.

Colorectal polyps in the colon or rectum are precancerous growths that can lead to a more severe disease called colorectal cancer. Accurate segmentati...