Fundus Picture AI testing
Diagnostic TestG-Risk AI algorithm will assess the optic disc centered fundus picture and determine whether or not there is a need for referrable based on a pre-determined threshold (>=0.73)
NCT Number: NCT06552247
Artificial Intelligence (AI) algorithms require validation in a variety of populations to ensure widespread clinical applicability. In Ophthalmology, AI algorithms are reaching maturity in diagnosis such as diabetic retinopathy and glaucoma. Higher-at-risk subjects of African descent are nevertheless usually under-represented in training datasets and therefore unclear about representativity.
A small scale validation study in consecutive patients in a large Eyesore unit in Mozambique will be performed to determine the diagnostic ability of these AI softwares in this population
Trial opening soon.
Get Notified18 year and older
All sexes
Interventional
Not applicable
Artificial Intelligence (AI) algorithm's are the next frontier in medical management, usually meant to improve diagnostic capabilities and to optimize the existing resources. They are particularly relevant in settings where there is a lack of specialised Human Resources such as physicians.
Ensuring these algorithms can be used in a wide population is therefore crucial to clinical implementation. Validation studies in specific segments of populations are needed to ensure all patients are represented and the results are therefore reliable. Higher-at-risk subjects of African descent are nevertheless usually under-represented in training datasets and therefore unclear about representativity.
A pilot study for validation of an AI algorithm for Glaucoma and Diabetic Retinopathy will be done for the MONA G-RISK® and diabetic retinopathy. Consecutive patients from a large Eye Unit in Mozambique's capital will be screened using these AI algorithms and validated using clinical standard as ground truth.
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
G-Risk AI algorithm will assess the optic disc centered fundus picture and determine whether or not there is a need for referrable based on a pre-determined threshold (>=0.73)
Time frame: Duration of the study - 3 weeks
Level of agreement will be done between referring decision and the ground truth as assessed by the reading center (normal, glaucoma suspect; definitive glaucoma). All subjects from both centers (referred and non-referred) will be reviewed.
For a primary outcome analysis, the middle category (glaucoma suspect) will be pooled together with the normal diagnosis
Time frame: After the study - 6 months
Reading center risk score of disease severity (ranked from 0 to 100) will be compared to the AI-based disease score. This will be done separately in each of the 3 categories (normal; glaucoma suspect; glaucoma). Analysis of this score would help refine clinical risk (high risk vs low risk patients) of each category. Exploratory analysis will be made to determine the added value of including this risk score in refining AI-based referral
Contact information is provided by the study sponsor or research team.
Luis Abegao Pinto, MD, PhD
CONTACT
Quirina Tavares Ferreira, PhD
CONTACT
Centro Hospitalar Universitário Lisboa Norte
Other
Validation Study of an Artificial Algorithm for Glaucoma Detection in an African Population
Acronym: MAGIC
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