Can we use artificial intelligence for microscopic parasite diagnosis?
Not Applicable
- Conditions
- Blood parasites (malaria, filaria and other NTDs such as Chagas disease and Leishmania)Infections and Infestations
- Registration Number
- ISRCTN98669958
- Lead Sponsor
- SpotLab S.L.
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Ongoing
- Sex
- Not specified
- Target Recruitment
- 209
Inclusion Criteria
1. All preparations likely to be positive for a parasite from the laboratory sample collection that are properly stained and where the morphology of the parasite is well preserved.
2. All preparations that have been previously anonymized without the possibility of reversing the coding.
Exclusion Criteria
1. All preparations that are not properly stained and the morphology of the parasite is not well preserved
2. All those preparations that have not been previously anonymized
Study & Design
- Study Type
- Observational
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method <br> 1. Standard procedure for remote analysis of digitized parasitological samples, measured by the number of samples analysed by web platform (TeleSpot) and analysis time per sample<br> 2. Repository of digitized parasite images with each parasitic form appearing in the image correctly marked and tagged measured by the number of tagged samples (images) for each parasitic form and % agreement among users (reviewers) throughout the study<br> 3. Accuracy of the AI algorithm developed measured by % of agreement among experts and AI algorithm throughout the study<br> 4. Usability report based on the results from SUS scale and specific product questionnaires evaluating the remote analysis process at the beginning and the end of the study<br>
- Secondary Outcome Measures
Name Time Method There are no secondary outcome measures