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

NCT05797064 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 460

Last updated 2023-04-04

No results posted yet for this study

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

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.

Sponsors & Collaborators

  • Sixth Affiliated Hospital, Sun Yat-sen University

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2023-06-01
Primary Completion
2026-06-01
Completion
2026-06-01

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05797064 on ClinicalTrials.gov