AIMC Topic: Esophageal Neoplasms

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Learning curve for robot-assisted Ivor Lewis esophagectomy.

Diseases of the esophagus : official journal of the International Society for Diseases of the Esophagus
This study aimed to demonstrate the learning curve of robot-assisted minimally invasive esophagectomy (RAMIE). A retrospective analysis of the first 124 consecutive patients who underwent RAMIE with intrathoracic anastomosis (Ivor Lewis) by a single ...

Convolutional neural network-based artificial intelligence for the diagnosis of early esophageal cancer based on endoscopic images: A meta-analysis.

Saudi journal of gastroenterology : official journal of the Saudi Gastroenterology Association
BACKGROUND: Early screening and treatment of esophageal cancer (EC) is particularly important for the survival and prognosis of patients. However, early EC is difficult to diagnose by a routine endoscopic examination. Therefore, convolutional neural ...

Using the da Vinci X® - System for Esophageal Surgery.

JSLS : Journal of the Society of Laparoendoscopic Surgeons
Robotic esophageal surgery is becoming more widely adopted. Several publications on the feasibility, short-term outcomes and technical aspects are available. Most of these articles used either the da Vinci® SI system or in newer series the Xi System....

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...

Accuracy of artificial intelligence-assisted detection of esophageal cancer and neoplasms on endoscopic images: A systematic review and meta-analysis.

Journal of digestive diseases
OBJECTIVE: To investigate systematically previous studies on the accuracy of artificial intelligence (AI)-assisted diagnostic models in detecting esophageal neoplasms on endoscopic images so as to provide scientific evidence for the effectiveness of ...

[Application and progress of artificial intelligence in endoscopic diagnosis of superficial esophageal cancer].

Zhonghua zhong liu za zhi [Chinese journal of oncology]
China is a country with high incidence of esophageal cancer. Advanced esophageal cancer not only brings serious threat to the health of patients, but also brings heavy economic burden to their families and society. Early diagnosis and treatment of es...

Clinical Target Volume Auto-Segmentation of Esophageal Cancer for Radiotherapy After Radical Surgery Based on Deep Learning.

Technology in cancer research & treatment
Radiotherapy plays an important role in controlling the local recurrence of esophageal cancer after radical surgery. Segmentation of the clinical target volume is a key step in radiotherapy treatment planning, but it is time-consuming and operator-de...

Artificial intelligence in upper GI endoscopy - current status, challenges and future promise.

Journal of gastroenterology and hepatology
White-light endoscopy with biopsy is the current gold standard modality for detecting and diagnosing upper gastrointestinal (GI) pathology. However, missed lesions remain a challenge. To overcome interobserver variability and learning curve issues, a...

Robot-assisted minimally invasive esophagectomy (RAMIE): tips and tricks from the bedside assistant view-expert experiences.

Diseases of the esophagus : official journal of the International Society for Diseases of the Esophagus
The role of bedside assistants in robot-assisted minimally invasive esophagectomy is important. It includes knowledge of the procedure, knowledge of the da Vinci Surgical System, skills in laparoscopy, and good communicative skills. An experienced be...