Skip to content

Segmentation and progress monitoring of chronic wounds using artificial intelligence (WUNDERKINT): Pilot study

Segmentation and progress monitoring of chronic wounds using artificial intelligence (WUNDERKINT): Pilot study - WUNDERKINT

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
DRKS
Registry ID
DRKS00038408
Enrollment
39
Registered
2025-11-13
Start date
2024-12-01
Completion date
Unknown
Last updated
2025-11-24

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

Conditions

Patients with chronic wounds

Interventions

Group 1: Patients with at least one chronic wound (lasting longer than 12 weeks) get access to the WUNDERKINT app, an AI-supported mobile application for documenting and monitoring chronic wounds. Usi
if there are any abnormal findings, feedback will be provided within 72 hours.

Sponsors

Universitätsklinikum Würzburg, Klinik für Dermatologie, Venerologie und Allergologie
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: - Presence of at least one chronic wound (existing for >12 weeks) - Capacity to give consent - Age over 18 - Access to a smartphone

Exclusion criteria

Exclusion criteria: - Under 18 years of age

Design outcomes

Primary

MeasureTime frame
Feasibility of app-based observational study, measured by regular use of the mobile application (“compliance”) over a period of 24 weeks. Regular use is defined as at least one application (uploading a wound image or entering progress parameters) per week over the entire observation period.

Secondary

MeasureTime frame
a. Safety and feasibility of app-based care (proportion of wound images evaluated, AE/SAE, video visits, uMARS feedback); b. Healing rate of chronic wounds (change in wound area manually and AI-based, proportion of completely healed wounds after 24 weeks); c. Change in quality of life and mental health (DLQI, WHO-5, HADS-A/D, PBI); d. Doctor-patient interaction and perceived benefit (PBI, uMARS); e. Technical feasibility and accuracy of AI segmentation (comparison of AI vs. manual measurement, technical success rate); f. Automated detection of complications (infection, increase in area).

Countries

Germany

Contacts

Public ContactAstrid Schmieder

Universitätsklinikum Würzburg, Klinik für Dermatologie, Venerologie und Allergologie

schmieder_a@ukw.de+4993120126710

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026