View abstract

Cet abstract a été assigné à session AOB Free Papers 2
Type de présentationOral presentation
TitreArtificial Intelligence Glaucoma Screening: Real-World Implementation and Validation
ButThis study evaluates whether artificial intelligence (AI) - based screening can detect asymptomatic patients and reduce morbidity.
MéthodesParticipants aged between 55-65 years identified from primary care databases were randomly invited to undergo glaucoma screening. Glaucoma risk was determined from the fundus image using an AI algorithm (MONA G-Risk®). Subjects were referred for further glaucoma assessment according to the AI’s outcome or an IOP of ≥24mmHg. Validation of the screening protocol was performed by reviewing the entire fundus photos dataset by six paired glaucoma experts. Referred participants performed visual field test as well as a face-to-face assessment with ophthalmologist.
RésultatsOf 1,038 subjects invited, 65% (671) were screened. The AI algorithm referred 9.8% (66/671) of participants while human-expert fundus review referred 77 more (143/671 or 21.3%). After excluding 42 who missed VF testing, 629 participants remained for analysis. Glaucoma was found in 6.4% (40/629; 95% CI 5–9%) and IOP ≥24 mmHg in 3.2% (20/629; 95% CI 2–5%). The AI algorithm’s sensitivity and specificity for detecting glaucoma were 78% (95% CI 62–89%) and 95% (95% CI 93–97%). The incremental cost-effectiveness ratio was €1,743 for the AI screening program implementation versus standard care scenario over a ten year horizon.
ConclusionGlaucoma screening with AI technology outperformed human detection. AI could boost screening efficiency and case detection, paving the basis for earlier treatment and avoidable blindness prevention.
Conflit d'intérêtNon
Détails conflits d'intérêtNone
Auteurs 1
InitialesA
NomCabrita
InstitutSanta Maria University Hospital, Lisbon
VilleLisbon
Auteurs 2
InitialesZ
NomWehbi
InstitutUZ Leuven, Belgium
VilleLeuven
Auteurs 3
InitialesI
NomStalmans
InstitutUZ Leuven, Belgium
VilleLeuven
Auteurs 4
InitialesL
NomPinto
InstitutSanta Maria University Hospital, Lisbon
VilleLisbon
top ^