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NCT05797064

Establishment of a Feasibility Model for NOSE Surgery Based on Machine Learning

Sponsor: Sixth Affiliated Hospital, Sun Yat-sen University

View on ClinicalTrials.gov

Summary

The goal of this observational study is to test in patients with resectable rectosigmoid cancers. The main question it aims to answer is establishment of a feasibility model for predicting natural orifice specimen extraction surgery (NOSES) based on machine learning.

Official title: Establishment of a Feasibility Model for Predicting Natural Orifice Specimen Extraction Surgery (NOSES) Based on Machine Learning.

Key Details

Gender

All

Age Range

18 Years - 80 Years

Study Type

OBSERVATIONAL

Enrollment

460

Start Date

2023-06-01

Completion Date

2026-06-01

Last Updated

2023-04-04

Healthy Volunteers

No

Interventions

PROCEDURE

Natural Orifice Specimen Extraction Surgery

Natural Orifice Specimen Extraction Surgery (NOSES) is a minimally invasive surgical technique that aims to reduce the size and number of incisions required during certain surgeries. In NOSES, the surgical specimen (such as a diseased organ or tumor) is removed from the body through a natural orifice (such as the mouth, anus, or vagina), rather than through an incision in the abdominal wall. In this trial, we will extract surgical specimens from the rectum to reduce trauma to the abdominal wall.

Locations (1)

The Sixth Affiliate Hospital of Sun Yat-Sen University

Guangzhou, Guangdong, China