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Using Artificial Intelligence to Predict Rectal Cancer Outcomes

NCT05723965 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 720

Last updated 2023-02-13

No results posted yet for this study

Summary

Investigator retrospective collect cases during 2010-2021 diagnosed as rectal adenocarcinoma with high quality CT images. Local advanced rectal cancer cases were labeled as "disease". Nor were defined " normal".

Using artificial intelligence CNN on jupyter notebook with open phyton code to train and develop models capable to recognizing local advanced rectal cancer. Modify the phyton code for better predict rate and help physician to quickly evaluate disease severity for fresh rectal cancer cases.

Conditions

  • Rectal Cancer Stage III

Interventions

OTHER

As training material for deep learning model.

Using labeled images as training materials for artificial intelligence to develop object detecting model.

OTHER

As materials for external validation for the buildup model.

Using the external validation set to evaluate prediction rate and survival outcome.

Sponsors & Collaborators

  • Taichung Veterans General Hospital

    lead OTHER

Principal Investigators

  • ChunuYu Lin, M.D. · Taichung Veterans General Hospital

Eligibility

Min Age
20 Years
Max Age
100 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2010-10-01
Primary Completion
2022-07-31
Completion
2022-12-31

Countries

  • Taiwan

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 NCT05723965 on ClinicalTrials.gov