Gastroenterology

Robotic esophagectomy and 3-field lymphadenectomy with intraoperative nerve monitoring.

The standard of care for esophageal malignancies has evolved over the years from open transthoracic esophagectomy to a minimally invasive approach due to the reduction in surgical trauma and significant impact on postoperative outcomes. Minimally invasive approaches include video-assisted thoracoscopic surgery and robot-assisted thoracoscopic surgery. These minimally invasive approaches have an at...

Operative and oncological outcomes after robotic rectal resection compared with laparoscopy: a systematic review and meta-analysis.

BACKGROUND: Most studies comparing robotic and laparoscopic surgery, show little difference in clinical outcomes to justify the expense. We systematically reviewed and pooled evidence from studies comparing robotic and laparoscopic rectal resection.

Implementation of the robotic abdominal phase during robot-assisted minimally invasive esophagectomy (RAMIE): results from a high-volume center.

BACKGROUND: Evidence on the added value of robotic-assistance in the abdominal phase during esophagectomy is scarce. In 2003, our center implemented t...

The Association of Waist Circumference with the Prevalence and Survival of Digestive Tract Cancer in US Adults: A Population Study Based on Machine Learning Methods.

AIMS: This paper aims to investigate the relationship of waist circumference (WC) with digestive tract cancer morbidity and mortality.

Robotic vs. laparoscopic intersphincteric resection for low rectal cancer: a case matched study reporting a median of 7-year long-term oncological and functional outcomes.

Aim of this study was to compare operative, long-term oncological and functional outcomes of laparoscopic (LISR) and robotic (RISR) intersphincteric r...

Design, Analysis and Experimental Validation of a Novel 7-Degrees of Freedom Instrument for Laparoscopic Surgeries.

Laparoscopic surgery is widely used for treating intra-abdominal conditions involving the gallbladder, pancreas, liver, intestines and reproductive or...

Reliably Filter Drug-Induced Liver Injury Literature With Natural Language Processing and Conformal Prediction.

Drug-induced liver injury describes the adverse effects of drugs that damage the liver. Life-threatening results were also reported in severe cases. T...

Robotic low anterior resection for locally advanced rectal cancer - A video vignette.

Deep learning-based automated quantification of goblet cell mucus using histological images as a predictor of clinical relapse of ulcerative colitis with endoscopic remission.

BACKGROUND: Mucin depletion is one of the histological indicators of clinical relapse among patients with ulcerative colitis (UC). Mucin depletion is ...

FBCU-Net: A fine-grained context modeling network using boundary semantic features for medical image segmentation.

The performance of deep learning-based medical image segmentation methods largely depends on the segmentation accuracy of tissue boundaries. However, ...

Prediction of Epstein-Barr Virus Status in Gastric Cancer Biopsy Specimens Using a Deep Learning Algorithm.

IMPORTANCE: Epstein-Barr virus (EBV)-associated gastric cancer (EBV-GC) is 1 of 4 molecular subtypes of GC and is confirmed by an expensive molecular ...

Artificial intelligence in pancreatic cancer.

Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of just 11%. The pancreatic cancer patients diagnosed with early sc...

Automatic Liver Tumor Segmentation on Dynamic Contrast Enhanced MRI Using 4D Information: Deep Learning Model Based on 3D Convolution and Convolutional LSTM.

OBJECTIVE: Accurate segmentation of liver tumors, which could help physicians make appropriate treatment decisions and assess the effectiveness of sur...

Perception without preconception: comparison between the human and machine learner in recognition of tissues from histological sections.

Deep neural networks (DNNs) have shown success in image classification, with high accuracy in recognition of everyday objects. Performance of DNNs has...

Integrative Histology-Genomic Analysis Predicts Hepatocellular Carcinoma Prognosis Using Deep Learning.

Cancer prognosis analysis is of essential interest in clinical practice. In order to explore the prognostic power of computational histopathology and ...

Robotic radical distal gastrectomy for gastric cancer using the soft coagulation scissors technique.

We have developed a novel technique for safe and precise lymph-node dissection during robotic gastrectomy for gastric cancer using monopolar curved sc...

Accelerated T2-weighted MRI of the liver at 3 T using a single-shot technique with deep learning-based image reconstruction: impact on the image quality and lesion detection.

PURPOSE: Fat-suppressed T2-weighted imaging (T2-FS) requires a long scan time and can be wrought with motion artifacts, urging the development of a sh...

Multistrategy Improved Sparrow Search Algorithm Optimized Deep Neural Network for Esophageal Cancer.

Deep neural network is a complex pattern recognition network system. It is widely favored by scholars for its strong nonlinear fitting ability. Howeve...

Primary Investigation of Deep Learning Models for Japanese "Group Classification" of Whole-Slide Images of Gastric Endoscopic Biopsy.

BACKGROUND: Accurate pathological diagnosis of gastric endoscopic biopsy could greatly improve the opportunity of early diagnosis and treatment of gas...

Automated clinical decision support system with deep learning dose prediction and NTCP models to evaluate treatment complications in patients with esophageal cancer.

BACKGROUND AND PURPOSE: This study aims to investigate how accurate our deep learning (DL) dose prediction models for intensity modulated radiotherapy...