Gastroenterology

Minimally Invasive Lower Anterior Resections - Better than Open But Not All the Same.

Optimal approach for lower anterior resection has been closely debated. The relatively new addition of the robotic approach adds a layer of complexity to this topic. The majority of the literature has compared the possible approaches between two techniques; however, only a few studies have comprehensively compared all 3 approaches at the same time, especially in a non-academic center. This is a r...

A one-dimensional convolutional neural network based deep learning for high accuracy classification of transformation stages in esophageal squamous cell carcinoma tissue using micro-FTIR.

Among the most frequently diagnosed cancers in developing countries, esophageal squamous cell carcinoma (ESCC) ranks among the top six causes of death. It would be beneficial if a rapid, accurate, and automatic ESCC diagnostic method could be developed to reduce the workload of pathologists and improve the effectiveness of cancer treatments. Using micro-FTIR spectroscopy, this study classified the...

Dual segmentation models for poorly and well-differentiated hepatocellular carcinoma using two-step transfer deep learning on dynamic contrast-enhanced CT images.

The aim of this study was to develop dual segmentation models for poorly and well-differentiated hepatocellular carcinoma (HCC), using two-step transf...

Robotic versus open pancreaticoduodenectomy in elderly patients: a propensity score-matched analysis.

BACKGROUND: Pancreaticoduodenectomy (PD) is complex procedure with high morbidity in the elderly. This retrospective study aimed to compare post-opera...

Introduction.

Endoscopic ultrasound (EUS) was born from the combination of a high-frequency ultrasound probe with an endoscope to assess in detail the walls of the ...

Computer-aided classification of colorectal segments during colonoscopy: a deep learning approach based on images of a magnetic endoscopic positioning device.

OBJECTIVE: Assessment of the anatomical colorectal segment of polyps during colonoscopy is important for treatment and follow-up strategies, but is la...

[Robot-assisted rectal resections-Scoping review for level 1a evidence and retrospective analysis of in-clinic data].

BACKGROUND: Robot-assisted rectal resections are said to overcome the known difficulties of laparoscopic rectal surgery through technical advantages, ...

Artificial intelligence model with deep learning in nonalcoholic fatty liver disease diagnosis: genetic based artificial neural networks.

Nonalcoholic fatty liver disease (NAFLD) is one of the most common causes of chronic liver disease in the world. The NAFLD spectrum includes simple st...

Efficacy and Safety of the "Trisection Method" Training System for Robot-Assisted Radical Cystectomy at a Single Institution in Japan.

To maintain a surgeon's concentration, reduce fatigue, and train young surgeons, surgical procedures for bladder cancer are divided into the following...

Improving liver lesions classification on CT/MRI images based on Hounsfield Units attenuation and deep learning.

The early sign detection of liver lesions plays an extremely important role in preventing, diagnosing, and treating liver diseases. In fact, radiologi...

Colon Cancer Diagnosis Based on Machine Learning and Deep Learning: Modalities and Analysis Techniques.

The treatment and diagnosis of colon cancer are considered to be social and economic challenges due to the high mortality rates. Every year, around th...

Crossroads in Liver Transplantation: Is Artificial Intelligence the Key to Donor-Recipient Matching?

Liver transplantation outcomes have improved in recent years. However, with the emergence of expanded donor criteria, tools to better assist donor-rec...

Uncertainty-aware physics-driven deep learning network for free-breathing liver fat and R * quantification using self-gated stack-of-radial MRI.

PURPOSE: To develop a deep learning-based method for rapid liver proton-density fat fraction (PDFF) and R * quantification with built-in uncertainty e...

Synchronous robotic repair of anterior diaphragmatic (Morgagni) hernia & low anterior resection for rectal cancer.

BACKGROUND: We present the case report of synchronous trans-fascial repair of a large congenital Morgagni hernia (MH) and low anterior resection using...

Setting up of a machine learning algorithm for the identification of severe liver fibrosis profile in the general US population cohort.

BACKGROUND: The progress of digital transformation in clinical practice opens the door to transforming the current clinical line for liver disease dia...

Deep learning model based on contrast-enhanced ultrasound for predicting early recurrence after thermal ablation of colorectal cancer liver metastasis.

OBJECTIVES: To develop and validate a deep learning (DL) model based on quantitative analysis of contrast-enhanced ultrasound (CEUS) images that predi...

Characterization of signature trends across the spectrum of non-alcoholic fatty liver disease using deep learning method.

AIMS: The timely diagnosis of different stages in NAFLD is crucial for disease treatment and reversal. We used hepatocellular ballooning to determine ...

Convolutional neural network based anatomical site identification for laryngoscopy quality control: A multicenter study.

OBJECTIVES: Video laryngoscopy is an important diagnostic tool for head and neck cancers. The artificial intelligence (AI) system has been shown to mo...

Contrast phase recognition in liver computer tomography using deep learning.

Hepatocellular carcinoma (HCC) has become the 4th leading cause of cancer-related deaths, with high social, economical and health implications. Imagin...

A Single-Institution Comparison of Robot-Assisted and Conventional Laparoscopic Colorectal Surgeries.

There has been ongoing discussion regarding the superiority of robotic laparoscopic surgery (RLS) over conventional laparoscopic surgery (CLS) in many...