Machine Learning Based Health Evaluation Using Retina Images and Recorded Pulse Waves

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00033094

Enrollment

100

Registered

2023-11-30

Start date

2023-11-23

Completion date

Unknown

Last updated

2025-04-07

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

Conditions

General health evaluation using a deep aging clock.

Interventions

Group 1: The observation group of the study consists of students who have already reached the age of 18. Both healthy students and students with pre-existing conditions can participate. Participants'

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: • Participation in the lecture "Machine Learning" at the Heinrich Heine University Düsseldorf . • Voluntary consent to participate in the study.

Exclusion criteria

Exclusion criteria: • Missing or withdrawn consent to participate in the study.

Design outcomes

Primary

Measure	Time frame
Inquiry of age, gender and diseases by a questionnaire, as well as retinal imaging and pulse waveform recording to predict the biological age	—

Countries

Germany

Contacts

Public ContactDominik Heider

Heinrich-Heine-Universität Düsseldorf

dominik.heider@hhu.de+49 211 81-13658

Outcome results

None listed

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