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Establishment of a Feasibility Model for NOSE Surgery Based on Machine Learning
Sponsor: Sixth Affiliated Hospital, Sun Yat-sen University
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
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