More than 200 images per clinician, subject to quality and eligibility review.
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.
Shared commercial participation among data-contributing clinicians, defined by agreement.
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
- 01
Retinopathy of Prematurity Detection and Staging
Ophthalmology
- 02
Malaria Parasite Detection and Species Classification
Parasitology
- 03
Diabetic Retinopathy Detection and Grading
Ophthalmology
- 04
Glaucoma Detection from Retinal Images
Ophthalmology
- 05
Cutaneous Leishmaniasis Detection
Dermatology / Parasitology
- 06
Intestinal Parasite Detection and Classification
Parasitology
- 07
Tuberculosis Detection in Sputum Microscopy
Microbiology
- 08
Automated Peripheral Blood Cell Classification
Hematology
- 09
Leukemia Detection from Peripheral Blood Smears
Hematology
- 10
Cervical Cytology Abnormality Detection
Cytopathology
- 11
Breast Cancer Histopathology Analysis
Pathology
- 12
Skin Cancer Detection from Dermoscopic Images
Dermatology
- 13
Diabetic Foot Ulcer Detection and Assessment
Wound Care
- 14
Pulmonary Tuberculosis Screening from Chest Radiographs
Radiology / Pulmonology
- 15
Pediatric Pneumonia Detection from Chest Radiographs
Pediatrics / Radiology
- 16
Breast Lesion Detection from Ultrasound Images
Radiology
- 17
Fetal Ultrasound Image Segmentation and Biometric Measurements
Obstetrics
- 18
Dental Caries Detection from Radiographs
Dentistry
- 19
Oral Cancer Screening from Clinical Photographs
Oral Medicine
- 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.comJorge Racedo · Biomedical engineer and principal investigator
