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Deep Learning Algorithm for Traumatic Splenic Injury Detection and Sequential Localization

NCT05643612 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 600

Last updated 2022-12-09

No results posted yet for this study

Summary

Spleen laceration is a lethal abdominal trauma and usually be diagnosed by medical images such as computed tomography. Deep learning had been proved its usage in detect abnormalities in medical images.

In this trial, we used de-identified registry databank to develop a novel deep-learning based algorithm to detect the spleen trauma and to identify the injury locations.

Conditions

  • Spleen Injury
  • Machine Learning

Interventions

DIAGNOSTIC_TEST

Deep learning algorithm

A sequential two-stage 3D spleen injury detection framework to identify splenic injury in the CT scans

Sponsors & Collaborators

  • Chang Gung Memorial Hospital

    lead OTHER

Principal Investigators

  • Chien-Hung Liao, MD. · Chang Gung Memorial Hospital

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2022-02-01
Primary Completion
2022-11-01
Completion
2022-11-01

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 NCT05643612 on ClinicalTrials.gov