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Esophageal Neoplasms

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Machine learning to predict curative multidisciplinary team treatment decisions in oesophageal cancer.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Rising workflow pressures within the oesophageal cancer (OC) multidisciplinary team (MDT) can lead to variability in decision-making, and health inequality. Machine learning (ML) offers a potential automated data-driven approach to addres...

Immediate Postoperative High Syndecan-1 is Associated with Short-Term Morbidity and Mortality After Robot-Assisted Esophagectomy: A Prospective Observational Study.

Annals of surgical oncology
BACKGROUND: Disruption of the endothelial glycocalyx (EG) is associated with a poor prognosis in various clinical settings. This study aimed to determine the association between immediate postoperative serum syndecan-1 levels, a representative marker...

Short-term outcomes of robot-assisted versus thoracoscopic-assisted Mckeown esophagectomy.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: Thoracoscopic-assisted and robot-assisted Mckeown esophagectomy are currently two common surgical methods, but there is no clear statement on the advantages and disadvantages of the two.

A novel staging system based on deep learning for overall survival in patients with esophageal squamous cell carcinoma.

Journal of cancer research and clinical oncology
PURPOSE: We developed DeepSurv, a deep learning approach for predicting overall survival (OS) in patients with esophageal squamous cell carcinoma (ESCC). We validated and visualized the novel staging system based on DeepSurv using data from multiple ...

Drainless robot-assisted minimally invasive oesophagectomy-randomized controlled trial (RESPECT).

Trials
BACKGROUND: The purpose of this randomized trial is to evaluate the early removal of postoperative drains after robot-assisted minimally invasive oesophagectomy (RAMIE). Evidence is lacking about feasibility, associated pain, recovery, and morbidity.

Towards a robust and compact deep learning system for primary detection of early Barrett's neoplasia: Initial image-based results of training on a multi-center retrospectively collected data set.

United European gastroenterology journal
INTRODUCTION: Endoscopic detection of early neoplasia in Barrett's esophagus is difficult. Computer Aided Detection (CADe) systems may assist in neoplasia detection. The aim of this study was to report the first steps in the development of a CADe sys...

Effects of deep learning on radiologists' and radiology residents' performance in identifying esophageal cancer on CT.

The British journal of radiology
OBJECTIVE: To investigate the effectiveness of a deep learning model in helping radiologists or radiology residents detect esophageal cancer on contrast-enhanced CT images.

Learning Curve of Robot-Assisted Lymph Node Dissection of the Left Recurrent Laryngeal Nerve: A Retrospective Study of 417 Patients.

Annals of surgical oncology
OBJECTIVE: Left recurrent laryngeal nerve (no.106recL) lymph node dissection is a challenging procedure, and robotic-assisted minimally invasive esophagectomy (RAMIE) may have some advantages. This study aimed to determine the learning curve of no.10...

[Robotic esophageal surgery].

Chirurgie (Heidelberg, Germany)
Robot-assisted minimally invasive esophagectomy (RAMIE) is increasingly becoming established as a standard procedure in surgical centers for esophagectomy in cases of cancer. To date, RAMIE has been shown to have fewer postoperative complications and...