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Application Value of Deep Learning in Diagnosis of Cervical Spondylosis

NCT04952233 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 2000

Last updated 2021-07-07

No results posted yet for this study

Summary

Compared with the personal experience judgment of physicians, deep learning can identify something more quickly, efficiently, and accurately The identification and diagnosis of diseases save the energy of clinical and imaging doctors and achieve an individualized diagnosis of patients Diagnosis and evaluation are beneficial to the formulation of clinical surgical methods and the improvement of patients' prognoses.

This study uses deep learning technology, through the big data of cervical spondylosis cases learn, to explore the use of deep learning The feasibility of identifying and analyzing the characteristic imaging findings of cervical CT images that may be suggestive of a diagnosis It is attempted to reach the level of artificial intelligence-assisted diagnosis of cervical spondylosis.

Conditions

  • Artificial Intelligence

Sponsors & Collaborators

  • Peking University Third Hospital

    lead OTHER

Principal Investigators

  • huishu yuan · Peking University Third Hospital

Eligibility

Min Age
18 Years
Max Age
80 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2021-01-30
Primary Completion
2021-06-30
Completion
2021-07-30

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 NCT04952233 on ClinicalTrials.gov