Gastroenterology

Optimization of robot-assisted thoracoscopic esophagectomy in the lateral decubitus position.

BACKGROUND: On the introduction of robot-assisted thoracoscopic esophagectomy (RATE), we refined the robotic system application to enhance our surgical experience obtained through thoracoscopic esophagectomy (TE) in the lateral decubitus position (LDP). Herein, we evaluate our methods introduced to optimize RATE in the LDP.

Dynamics of Systemic Inflammation as a Function of Developmental Stage in Pediatric Acute Liver Failure.

The Pediatric Acute Liver Failure (PALF) study is a multicenter, observational cohort study of infants and children diagnosed with this complex clinical syndrome. Outcomes in PALF reflect interactions among the child's clinical condition, response to supportive care, disease severity, potential for recovery, and, if needed, availability of a suitable organ for liver transplantation (LTx). Previous...

Preoperative classification of primary and metastatic liver cancer via machine learning-based ultrasound radiomics.

OBJECTIVE: To investigate the application of machine learning-based ultrasound radiomics in preoperative classification of primary and metastatic live...

Real-time liver tracking algorithm based on LSTM and SVR networks for use in surface-guided radiation therapy.

BACKGROUND: Surface-guided radiation therapy can be used to continuously monitor a patient's surface motions during radiotherapy by a non-irradiating,...

Machine learning predicts lymph node metastasis of poorly differentiated-type intramucosal gastric cancer.

To construct a machine learning algorithm model of lymph node metastasis (LNM) in patients with poorly differentiated-type intramucosal gastric cancer...

Improving prognostic performance in resectable pancreatic ductal adenocarcinoma using radiomics and deep learning features fusion in CT images.

As an analytic pipeline for quantitative imaging feature extraction and analysis, radiomics has grown rapidly in the past decade. On the other hand, r...

Establishing key research questions for the implementation of artificial intelligence in colonoscopy: a modified Delphi method.

BACKGROUND : Artificial intelligence (AI) research in colonoscopy is progressing rapidly but widespread clinical implementation is not yet a reality. ...

Gut microbiome-based supervised machine learning for clinical diagnosis of inflammatory bowel diseases.

Despite the availability of various diagnostic tests for inflammatory bowel diseases (IBD), misdiagnosis of IBD occurs frequently, and thus, there is ...

Optimization of probiotic therapeutics using machine learning in an artificial human gastrointestinal tract.

The gut microbiota's metabolome is composed of bioactive metabolites that confer disease resilience. Probiotics' therapeutic potential hinges on their...

Use of BERT (Bidirectional Encoder Representations from Transformers)-Based Deep Learning Method for Extracting Evidences in Chinese Radiology Reports: Development of a Computer-Aided Liver Cancer Diagnosis Framework.

BACKGROUND: Liver cancer is a substantial disease burden in China. As one of the primary diagnostic tools for detecting liver cancer, dynamic contrast...

An ensemble learning approach for modeling the systems biology of drug-induced injury.

BACKGROUND: Drug-induced liver injury (DILI) is an adverse reaction caused by the intake of drugs of common use that produces liver damage. The impact...

Research on Early Warning Mechanism and Model of Liver Cancer Rehabilitation Based on CS-SVM.

Since the 20 century, cancer has become one of the main diseases threatening human health. Liver cancer is a malignant tumor with extremely high clini...

Multi disease-prediction framework using hybrid deep learning: an optimal prediction model.

Big data and its approaches are generally helpful for healthcare and biomedical sectors for predicting the disease. For trivial symptoms, the difficul...

A Machine Learning Approach Yields a Multiparameter Prognostic Marker in Liver Cancer.

A number of staging systems have been developed to predict clinical outcomes in hepatocellular carcinoma (HCC). However, no general consensus has been...

Analyzing Surgical Treatment of Intestinal Obstruction in Children with Artificial Intelligence.

Intestinal obstruction is a common surgical emergency in children. However, it is challenging to seek appropriate treatment for childhood ileus since ...

Integration of human cell lines gene expression and chemical properties of drugs for Drug Induced Liver Injury prediction.

MOTIVATION: Drug-induced liver injury (DILI) is one of the primary problems in drug development. Early prediction of DILI can bring a significant redu...

Robotic transanal minimally invasive surgery: a case series.

INTRODUCTION: This study describes the experience with robot-assisted transanal minimally invasive surgery (rTAMIS) at a single institution. TAMIS has...

Convolutional autoencoder based model HistoCAE for segmentation of viable tumor regions in liver whole-slide images.

Liver cancer is one of the leading causes of cancer deaths in Asia and Africa. It is caused by the Hepatocellular carcinoma (HCC) in almost 90% of all...

Development of artificial intelligence system for quality control of photo documentation in esophagogastroduodenoscopy.

BACKGROUND: Esophagogastroduodenoscopy (EGD) is generally a safe procedure, but adverse events often occur. This highlights the necessity of the quali...

Short-term outcome after robot-assisted hiatal hernia and anti-reflux surgery-is there a benefit for the patient?

PURPOSE: The robotic system was introduced to overcome the technical limitations of conventional laparoscopy. For complex oncological operations, it a...