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Medical records based study of deep learning in diagnosis of ear diseases

Study of deep learning in diagnosis of ear diseases

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2000036300
Enrollment
Unknown
Registered
2020-08-22
Start date
2020-09-01
Completion date
Unknown
Last updated
2020-09-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

ear diseases

Interventions

Gold Standard:Clinical outcome
Index test:deep-learning&#32
framework

Sponsors

Eye & ENT hospital of Fudan University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Patients who underwent ear surgery and had complete case data (history, audiogram, tympanic membrane image, CT and surgical records) were included in our hospital

Exclusion criteria

Exclusion criteria: Patients who underwent ear surgery and didn't have complete case data (history, audiogram, tympanic membrane image, CT and surgical records) were excluded in our hospital

Design outcomes

Primary

MeasureTime frame
ACC, SEN, SPE, AUC of ROC;—

Countries

China

Contacts

Public ContactDongdong Ren

Eye & ENT hospital of Fudan University

dongdong_ren@163.com+86 13801913332

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 6, 2026