NCT05797064

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

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

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 460 (estimated)
• Sponsor: Sixth Affiliated Hospital, Sun Yat-sen University · Academic / Other
• Sex: All
• Age: 18 Years – 80 Years
• Healthy volunteers: Not accepted

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.

Conditions

• Machine Learning
• Surgery
• Rectosigmoid Cancer
• Natural Orifice Specimen Extraction Surgery

Interventions

Type	Name	Description
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.

Timeline

• Start date: 2023-06-01
• Primary completion: 2026-06-01
• Completion: 2026-06-01
• First posted: 2023-04-04
• Last updated: 2023-04-04

Locations

1 site across 1 country: China