AI-Driven Analysis of Menstrual Blood: Diagnosing Endometriosis through Image Processing

AI-Driven Analysis of Menstrual Blood: Diagnosing Endometriosis through Image Processing - MAI (Menstrual Blood AI)

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

DRKS

Registry ID

DRKS00036558

Enrollment

2150

Registered

2025-05-19

Start date

2025-05-30

Completion date

Unknown

Last updated

2025-10-06

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

Conditions

N80

Interventions

Group 1: Online study and interviews with menstruating individuals without diagnosed endometriosis

Eligibility

Sex/Gender

All

Age

18 Years to 55 Years

Inclusion criteria

Inclusion criteria: - Individuals who experience a menstrual cycle without known gynaecological diagnosis - Individuals who experience a menstrual cycle with gynaecologically confirmed endometriosis - Individuals who experience a menstrual cycle with suspected endometriosis - Willingness to accept the consent for participation in the study

Exclusion criteria

Exclusion criteria: - Individuals, younger than 18 years old and older than 55 years old - Individuals, who have a different gynaecological diagnosis than endometriosis - Individuals, who do not experience a menstrual cycle

Design outcomes

Primary

Measure	Time frame
Development and validation of a machine learning algorithm capable of accurately classifying menstrual blood images for potential endometriosis diagnosis.	—

Secondary

Measure	Time frame
Evaluation of public and gynaecologists’ perceptions, attitudes, and acceptability of menstrual blood-based diagnostics.	—

Countries

Germany

Contacts

Public ContactRuth Niedermeier

LMU Klinikum, Insitut für Infektions und Tropenmedizin

ruth.niedermeier@med.uni-muenchen.de004917661809275

Outcome results

None listed

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