OPEN CALL · CLINICAL COLLABORATION

Help AI learn from clinical expertise.

We invite clinicians with more than 200 authorized images, without identifiable or confidential information, to collaborate across 20 AI research tracks.

200+

More than 200 images per clinician, subject to quality and eligibility review.

30%

Shared commercial participation among data-contributing clinicians, defined by agreement.

Before 20 Oct.

Expected delivery before 20 October 2026, after agreements and required permissions.

A scientific collaboration with clear responsibilities.

Jorge Racedo, biomedical engineer, is the principal investigator for all 20 tracks. These are research projects: their titles describe development objectives, not approved diagnostic tools or guaranteed results.

Authorized, secure data

Depending on the track, images may include digitized specimens, microscopy, radiographs, ultrasound, clinical photographs or ECGs. Do not send physical biological specimens. Remove identifiers from pixels, filenames, DICOM/EXIF metadata, dates, labels, faces and other identifying features. Coding is not anonymization. Do not transfer re-identification keys.

Possession does not establish ownership or permission. Institutional authorization and an ethical and legal basis for research, training and potential commercial use are required. We agree a secure transfer route and verify de-identification before admitting data. Do not attach images to the initial email.

Clinicians who train teams

An assigned student group will work with each accepted clinician to learn pattern recognition, image labeling and data preparation. The clinician supervises labeling criteria, annotations and disagreements; students do not make independent clinical decisions.

The protocol defines reference standards, quality, duplicate cases, patient-level separation of training and evaluation, diversity, bias assessment and validation. Data acceptance depends on these requirements and project feasibility.

Authorship through contribution

Clinicians participate as scientific collaborators with an opportunity for authorship in resulting manuscripts when they meet contribution and editorial responsibilities: substantial contribution, drafting or critical revision, final approval and accountability. Images alone do not guarantee authorship. Contributions and author order will be documented transparently.

A shared 30% commercial participation

microscopIA offers a collective 30% economic participation in commercial exploitation of the relevant AI, distributed among clinicians contributing data to that project. It is not 30% per clinician, company equity or a guaranteed return.

Before data transfer, the agreement must define the calculation base (receipts and expressly agreed deductions), allocation among clinicians, covered products and licences, term, payments, reports, accounting verification, taxes, termination and institutional rights. No definition of net proceeds or unilateral deductions is presumed. Without a signed agreement, data transfer and the project do not begin.

RESEARCH PORTFOLIO

20 tracks open for collaboration

  1. 01

    Retinopathy of Prematurity Detection and Staging

    Ophthalmology

  2. 02

    Malaria Parasite Detection and Species Classification

    Parasitology

  3. 03

    Diabetic Retinopathy Detection and Grading

    Ophthalmology

  4. 04

    Glaucoma Detection from Retinal Images

    Ophthalmology

  5. 05

    Cutaneous Leishmaniasis Detection

    Dermatology / Parasitology

  6. 06

    Intestinal Parasite Detection and Classification

    Parasitology

  7. 07

    Tuberculosis Detection in Sputum Microscopy

    Microbiology

  8. 08

    Automated Peripheral Blood Cell Classification

    Hematology

  9. 09

    Leukemia Detection from Peripheral Blood Smears

    Hematology

  10. 10

    Cervical Cytology Abnormality Detection

    Cytopathology

  11. 11

    Breast Cancer Histopathology Analysis

    Pathology

  12. 12

    Skin Cancer Detection from Dermoscopic Images

    Dermatology

  13. 13

    Diabetic Foot Ulcer Detection and Assessment

    Wound Care

  14. 14

    Pulmonary Tuberculosis Screening from Chest Radiographs

    Radiology / Pulmonology

  15. 15

    Pediatric Pneumonia Detection from Chest Radiographs

    Pediatrics / Radiology

  16. 16

    Breast Lesion Detection from Ultrasound Images

    Radiology

  17. 17

    Fetal Ultrasound Image Segmentation and Biometric Measurements

    Obstetrics

  18. 18

    Dental Caries Detection from Radiographs

    Dentistry

  19. 19

    Oral Cancer Screening from Clinical Photographs

    Oral Medicine

  20. 20

    Electrocardiogram Arrhythmia Detection and Classification

    Cardiology

First, tell us about your collection.

Send your name, specialty, institution, country, tracks of interest, image count and modality, and permission status. Include no patient information. Confidentiality, research, responsible-use, data and commercial-participation agreements are signed before starting. If permissions are not ready, do not transfer data just to meet the deadline.

jorge.racedo@microscopiatech.com

Jorge Racedo · Biomedical engineer and principal investigator