Gastroenterology

Detection of multiple lesions of gastrointestinal tract for endoscopy using artificial intelligence model: a pilot study.

BACKGROUND: This study was aimed to develop a computer-aided diagnosis (CAD) system with deep-learning technique and to validate its efficiency on detecting the four categories of lesions such as polyps, advanced cancer, erosion/ulcer and varices at endoscopy.

A deep learning framework for quality assessment and restoration in video endoscopy.

Endoscopy is a routine imaging technique used for both diagnosis and minimally invasive surgical treatment. Artifacts such as motion blur, bubbles, specular reflections, floating objects and pixel saturation impede the visual interpretation and the automated analysis of endoscopy videos. Given the widespread use of endoscopy in different clinical applications, robust and reliable identification of...

Comparison of Therapeutic Effects Among Different Surgical Approaches in Robot-Assisted Partial Nephrectomy: A Systematic Review and Meta-Analysis.

To systematically explore the superiority of the transperitoneal approach in robot-assisted partial nephrectomy (TP-RAPN) and retroperitoneal approac...

A real-time system using deep learning to detect and track ureteral orifices during urinary endoscopy.

BACKGROUND AND OBJECTIVE: To automatically identify and locate various types and states of the ureteral orifice (UO) in real endoscopy scenarios, we d...

Initial introduction of robot-assisted, minimally invasive esophagectomy using the microanatomy-based concept in the upper mediastinum.

BACKGROUND: We have recently standardized upper mediastinal lymph node dissection (UMLND) using a microanatomy-based concept in thoracoscopic esophage...

A Prospective Validation and Observer Performance Study of a Deep Learning Algorithm for Pathologic Diagnosis of Gastric Tumors in Endoscopic Biopsies.

PURPOSE: Gastric cancer remains the leading cause of cancer-related deaths in Northeast Asia. Population-based endoscopic screenings in the region hav...

Early gastric cancer and Artificial Intelligence: Is it time for population screening?

Gastric cancer is a common cause of death worldwide and its early detection is crucial to improve its prognosis. Its incidence varies throughout count...

Artificial intelligence in musculoskeletal oncological radiology.

BACKGROUND: Due to the rarity of primary bone tumors, precise radiologic diagnosis often requires an experienced musculoskeletal radiologist. In order...

Worldwide Techniques and Outcomes in Robot-assisted Minimally Invasive Esophagectomy (RAMIE): Results From the Multicenter International Registry.

OBJECTIVE: This international multicenter study by the Upper GI International Robotic Association aimed to gain insight in current techniques and outc...

Using chatbots to screen for heritable cancer syndromes in patients undergoing routine colonoscopy.

BACKGROUND: Hereditary colorectal cancer (HCRC) syndromes account for 10% of colorectal cancers but remain underdiagnosed. This feasibility project te...

Intelligent difficulty scoring and assistance system for endoscopic extraction of common bile duct stones based on deep learning: multicenter study.

BACKGROUND: The study aimed to construct an intelligent difficulty scoring and assistance system (DSAS) for endoscopic retrograde cholangiopancreatogr...

Safety and efficacy of robot-assisted versus open pancreaticoduodenectomy: a meta-analysis of multiple worldwide centers.

The objective of the study is to compare the safety and efficacy of robot-assisted pancreaticoduodenectomy (PD) with open PD. The PubMed, EMBASE and C...

Deep learning-enabled multi-organ segmentation in whole-body mouse scans.

Whole-body imaging of mice is a key source of information for research. Organ segmentation is a prerequisite for quantitative analysis but is a tediou...

Robotic versus open oncological gastric surgery in the elderly: a propensity score-matched analysis.

Although there is no agreement on a definition of elderly, commonly an age cutoff of ≥ 65 or 75 years is used. Even if robot-assisted surgery is a val...

Artificial intelligence automates and augments baseline impedance measurements from pH-impedance studies in gastroesophageal reflux disease.

BACKGROUND: Artificial intelligence (AI) has potential to streamline interpretation of pH-impedance studies. In this exploratory observational cohort ...

Deep learning networks on chronic liver disease assessment with fine-tuning of shear wave elastography image sequences.

Chronic liver disease (CLD) is currently one of the major causes of death worldwide. If not treated, it may lead to cirrhosis, hepatic carcinoma and d...

Identification of early liver toxicity gene biomarkers using comparative supervised machine learning.

Screening agrochemicals and pharmaceuticals for potential liver toxicity is required for regulatory approval and is an expensive and time-consuming pr...

Fully-automated functional region annotation of liver via a 2.5D class-aware deep neural network with spatial adaptation.

BACKGROUND AND OBJECTIVE: Automatic functional region annotation of liver should be very useful for preoperative planning of liver resection in the cl...

Host variables confound gut microbiota studies of human disease.

Low concordance between studies that examine the role of microbiota in human diseases is a pervasive challenge that limits the capacity to identify ca...

Artificial intelligence in endoscopy: Present and future perspectives.

Artificial intelligence (AI) has been attracting considerable attention as an important scientific topic in the field of medicine. Deep-leaning (DL) t...