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Construction and application of an intelligent measurement model of diabetic foot ulcer area based on deep learning

Research and development of intelligent measurement technology and standardized treatment platform for diabetic foot ulcer based on deep learning

Status
Recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2100047210
Enrollment
Unknown
Registered
2021-06-11
Start date
2021-07-01
Completion date
Unknown
Last updated
2022-01-24

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

Conditions

Diabetic foot ulcer

Interventions

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Sponsors

Xiangya Hospital, Central South University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1. It was in line with the diagnostic criteria of diabetes formulated by ADA in 1999, and it was in line with grade 1-4 of Wagner grade of diabetic foot; 2. Meet the requirements of APP photography (see Appendix 2); 3. Voluntarily participate in this investigation and study, and sign the informed consent.

Exclusion criteria

Exclusion criteria: 1. There are ulcers of stealth, sinus tract and fistula; 2. People suffering from mental illness or consciousness disturbance.

Design outcomes

Primary

MeasureTime frame
Measurement results of ulcer area;Measuring time;SEN, SPE, ACC, AUC of ROC;—

Countries

China

Contacts

Public ContactZhou Qiuhong

Xiangya Hospital, Central South University

928555448@qq.com+86 13786136512

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 8, 2026