Gastroenterology

NucleiSegNet: Robust deep learning architecture for the nuclei segmentation of liver cancer histopathology images.

The nuclei segmentation of hematoxylin and eosin (H&E) stained histopathology images is an important prerequisite in designing a computer-aided diagnostics (CAD) system for cancer diagnosis and prognosis. Automated nuclei segmentation methods enable the qualitative and quantitative analysis of tens of thousands of nuclei within H&E stained histopathology images. However, a major challenge during n...

Robotic Vaginal Natural Orifice Transluminal Endoscopic Hysterectomy for Benign Indications.

STUDY OBJECTIVE: The Hominis surgical system is a novel robot-assisted system, designed specifically for robotic vaginal natural orifice transluminal endoscopic surgery (RvNOTES). We presented our experience of the first 30 RvNOTES hysterectomies assessing the feasibility and safety of this technology.

Formal robotic training diminishes the learning curve for robotic pancreatoduodenectomy: Implications for new programs in complex robotic surgery.

INTRODUCTION: The learning curve associated with robotic pancreatoduodenectomy (RPD) is a hurdle for new programs to achieve optimal results. Since ea...

Development, Validation, and Evaluation of a Simple Machine Learning Model to Predict Cirrhosis Mortality.

IMPORTANCE: Machine-learning algorithms offer better predictive accuracy than traditional prognostic models but are too complex and opaque for clinica...

Use of Artificial Intelligence Deep Learning to Determine the Malignant Potential of Pancreatic Cystic Neoplasms With Preoperative Computed Tomography Imaging.

BACKGROUND: Society consensus guidelines are commonly used to guide management of pancreatic cystic neoplasms (PCNs). However, downsides of these guid...

An index based on deep learning-measured spleen volume on CT for the assessment of high-risk varix in B-viral compensated cirrhosis.

OBJECTIVES: Deep learning enables an automated liver and spleen volume measurements on CT. The purpose of this study was to develop an index combining...

Artificial intelligence that determines the clinical significance of capsule endoscopy images can increase the efficiency of reading.

Artificial intelligence (AI), which has demonstrated outstanding achievements in image recognition, can be useful for the tedious capsule endoscopy (C...

A deep learning framework for pancreas segmentation with multi-atlas registration and 3D level-set.

In this paper, we propose and validate a deep learning framework that incorporates both multi-atlas registration and level-set for segmenting pancreas...

Layer Embedding Analysis in Convolutional Neural Networks for Improved Probability Calibration and Classification.

In this project, our goal is to develop a method for interpreting how a neural network makes layer-by-layer embedded decisions when trained for a clas...

A Gratifying Step forward for the Application of Artificial Intelligence in the Field of Endoscopy: A Narrative Review.

BACKGROUND: Endoscopy is the optimal choice of diagnosis of gastrointestinal (GI) diseases. Following the advancements made in medical technology, dif...

Diagnosis of gastric lesions through a deep convolutional neural network.

BACKGROUND AND AIMS: A deep convolutional neural network (CNN) was used to achieve fast and accurate artificial intelligence (AI)-assisted diagnosis o...

Advanced Imaging and Sampling in Barrett's Esophagus: Artificial Intelligence to the Rescue?

Because the current Barrett's esophagus (BE) surveillance protocol suffers from sampling error of random biopsies and a high miss-rate of early neopla...

Development of a susceptibility gene based novel predictive model for the diagnosis of ulcerative colitis using random forest and artificial neural network.

Ulcerative colitis is a type of inflammatory bowel disease characterized by chronic and recurrent nonspecific inflammation of the intestinal tract. To...

Infusion of short chain fatty acids in the ileum improves the carcass traits, meat quality and lipid metabolism of growing pigs.

Short chain fatty acids (SCFA) are the main products of indigestible carbohydrates undergoing bacterial fermentation in the hindgut, which are related...

Robot-assisted extraperitoneal para-aortic lymphadenectomy (RAePAL) performed with the bipolar cutting method.

OBJECTIVE: In comparison with laparoscopic transperitoneal para-aortic lymphadenectomy, the advantages of laparoscopic extraperitoneal para-aortic lym...

Enhanced Image-Based Endoscopic Pathological Site Classification Using an Ensemble of Deep Learning Models.

In vivo diseases such as colorectal cancer and gastric cancer are increasingly occurring in humans. These are two of the most common types of cancer t...

Development of a Malignancy Potential Binary Prediction Model Based on Deep Learning for the Mitotic Count of Local Primary Gastrointestinal Stromal Tumors.

OBJECTIVE: The mitotic count of gastrointestinal stromal tumors (GIST) is closely associated with the risk of planting and metastasis. The purpose of ...

Central Reading of Ulcerative Colitis Clinical Trial Videos Using Neural Networks.

BACKGROUND AND AIMS: Endoscopic disease activity scoring in ulcerative colitis (UC) is useful in clinical practice but done infrequently. It is requir...

Predicting voxel-level dose distributions for esophageal radiotherapy using densely connected network with dilated convolutions.

This work aims to develop a voxel-level dose prediction framework by integrating distance information between PTV and OARs, as well as image informati...

Surgical technique for mesorectal division during robot-assisted laparoscopic tumor-specific mesorectal excision (TSME) for rectal cancer using da Vinci Si surgical system: the simple switching technique (SST).

In a narrow pelvic cavity, performing sufficient tumor-specific mesorectal excision (TSME) is difficult. Even in robot-assisted laparoscopic surgery (...