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Esophageal Squamous Cell Carcinoma

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Computed tomography-based deep-learning prediction of neoadjuvant chemoradiotherapy treatment response in esophageal squamous cell carcinoma.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND: Deep learning is promising to predict treatment response. We aimed to evaluate and validate the predictive performance of the CT-based model using deep learning features for predicting pathologic complete response to neoadjuvant chemoradi...

3D Deep Learning Model for the Pretreatment Evaluation of Treatment Response in Esophageal Carcinoma: A Prospective Study (ChiCTR2000039279).

International journal of radiation oncology, biology, physics
PURPOSE: To develop and validate a pretreatment computed tomography (CT)-based deep-learning (DL) model for predicting the treatment response to concurrent chemoradiation therapy (CCRT) among patients with locally advanced thoracic esophageal squamou...

Using a machine learning approach to identify key prognostic molecules for esophageal squamous cell carcinoma.

BMC cancer
BACKGROUND: A plethora of prognostic biomarkers for esophageal squamous cell carcinoma (ESCC) that have hitherto been reported are challenged with low reproducibility due to high molecular heterogeneity of ESCC. The purpose of this study was to ident...

A Novel Deep Learning System for Diagnosing Early Esophageal Squamous Cell Carcinoma: A Multicenter Diagnostic Study.

Clinical and translational gastroenterology
INTRODUCTION: This study aims to construct a real-time deep convolutional neural networks (DCNNs) system to diagnose early esophageal squamous cell carcinoma (ESCC) with white light imaging endoscopy.

Artificial intelligence for detecting superficial esophageal squamous cell carcinoma under multiple endoscopic imaging modalities: A multicenter study.

Journal of gastroenterology and hepatology
BACKGROUND AND AIM: Diagnosis of esophageal squamous cell carcinoma (ESCC) is complicated and requires substantial expertise and experience. This study aimed to develop an artificial intelligence (AI) system for detecting superficial ESCC under multi...

Feasibility and Accuracy of Artificial Intelligence-Assisted Sponge Cytology for Community-Based Esophageal Squamous Cell Carcinoma Screening in China.

The American journal of gastroenterology
INTRODUCTION: Screening is the pivotal strategy to relieve the burden of esophageal squamous cell carcinoma (ESCC) in high-risk areas. The cost, invasiveness, and accessibility of esophagogastroduodenoscopy (EGD) necessitate the development of prelim...

Robot-assisted Versus Conventional Minimally Invasive Esophagectomy for Resectable Esophageal Squamous Cell Carcinoma: Early Results of a Multicenter Randomized Controlled Trial: the RAMIE Trial.

Annals of surgery
OBJECTIVE: To compare perioperative and long-term outcomes of robot-assisted minimally invasive esophagectomy (RAMIE) and conventional minimally invasive esophagectomy (MIE) in the treatment for patients with esophageal squamous cell carcinoma (ESCC)...

A prediction model for pathological findings after neoadjuvant chemoradiotherapy for resectable locally advanced esophageal squamous cell carcinoma based on endoscopic images using deep learning.

The British journal of radiology
OBJECTIVES: To propose deep-learning (DL)-based predictive model for pathological complete response rate for resectable locally advanced esophageal squamous cell carcinoma (SCC) after neoadjuvant chemoradiotherapy (NCRT) with endoscopic images.

Deep-learning-based classification of desmoplastic reaction on H&E predicts poor prognosis in oesophageal squamous cell carcinoma.

Histopathology
AIMS: Desmoplastic reaction (DR) categorisation has been shown to be a promising prognostic factor in oesophageal squamous cell carcinoma (ESCC). The usual DR evaluation is performed using semiquantitative scores, which can be subjective. This study ...