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Automated Diagnosis of Stroke in Computed Tomography With the Use of Artificial Intelligence

NCT03874702 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 350

Last updated 2021-05-18

No results posted yet for this study

Summary

The use of the systems of machine learning for the quantification, location and diagnosis of ischemic stroke in non-contrasted head computed tomography, is a method with high efficacy, accessible and susceptible for standardization, for the assistance in the clinical decision making in the absence of specialized health personnel for the attention of this disease.

Conditions

Sponsors & Collaborators

  • University of Guadalajara

    lead OTHER

Principal Investigators

  • Rodrigo Ramos Zúñiga, M.D. Ph.D. · University of Guadalajara

  • Eduardo Gerardo Mendizábal Ruiz, Ph.D. · University of Guadalajara

  • José Luis Ruiz Sandoval, M.D. · University of Guadalajara

  • Ivan Segura Duran, M.D. · University of Guadalajara

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2019-08-15
Primary Completion
2025-06-01
Completion
2025-06-01

Countries

  • Mexico

Study Locations

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Entities

Diseases

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 NCT03874702 on ClinicalTrials.gov