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http://hdl.handle.net/1942/39967
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DC Field | Value | Language |
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dc.contributor.author | Peeters, Freya | - |
dc.contributor.author | Rommes, Stef | - |
dc.contributor.author | Elen, Bart | - |
dc.contributor.author | Gerrits, Nele | - |
dc.contributor.author | Stalmans, Ingeborg | - |
dc.contributor.author | Jacob, Julie | - |
dc.contributor.author | DE BOEVER, Patrick | - |
dc.date.accessioned | 2023-04-24T11:17:33Z | - |
dc.date.available | 2023-04-24T11:17:33Z | - |
dc.date.issued | 2023 | - |
dc.date.submitted | 2023-04-05T14:47:31Z | - |
dc.identifier.citation | Journal of Clinical Medicine, 12 (4) (Art N° 1408) | - |
dc.identifier.uri | http://hdl.handle.net/1942/39967 | - |
dc.description.abstract | Aim: To evaluate the MONA.health artificial intelligence screening software for detecting referable diabetic retinopathy (DR) and diabetic macular edema (DME), including subgroup analysis. Methods: The algorithm's threshold value was fixed at the 90% sensitivity operating point on the receiver operating curve to perform the disease classification. Diagnostic performance was appraised on a private test set and publicly available datasets. Stratification analysis was executed on the private test set considering age, ethnicity, sex, insulin dependency, year of examination, camera type, image quality, and dilatation status. Results: The software displayed an area under the curve (AUC) of 97.28% for DR and 98.08% for DME on the private test set. The specificity and sensitivity for combined DR and DME predictions were 94.24 and 90.91%, respectively. The AUC ranged from 96.91 to 97.99% on the publicly available datasets for DR. AUC values were above 95% in all subgroups, with lower predictive values found for individuals above the age of 65 (82.51% sensitivity) and Caucasians (84.03% sensitivity). Conclusion: We report good overall performance of the MONA.health screening software for DR and DME. The software performance remains stable with no significant deterioration of the deep learning models in any studied strata. | - |
dc.description.sponsorship | This research was performed with the support of the Eureka PENTA program and VLAIO (HBC.2019.2714) and by intramural funds from VITO and UZ Leuven. We appreciate the initial developments of the algorithms by Toon Van Craenendonck and software programming by Pieter Verberck during their employment at VITO. | - |
dc.language.iso | en | - |
dc.publisher | MDPI | - |
dc.rights | 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). | - |
dc.subject.other | diabetes complication | - |
dc.subject.other | diabetic retinopathy | - |
dc.subject.other | retina | - |
dc.subject.other | artificial intelligence | - |
dc.subject.other | deep learning | - |
dc.title | Artificial Intelligence Software for Diabetic Eye Screening: Diagnostic Performance and Impact of Stratification | - |
dc.type | Journal Contribution | - |
dc.identifier.issue | 4 | - |
dc.identifier.volume | 12 | - |
local.format.pages | 19 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | Peeters, F (corresponding author), Univ Hosp Leuven, Dept Ophthalmol, B-3000 Leuven, Belgium.; Peeters, F (corresponding author), Katholieke Univ Leuven, Dept Neurosci, Biomed Sci Grp, Res Grp Ophthalmol, B-3000 Leuven, Belgium. | - |
dc.description.notes | freya.peeters@uzleuven.be | - |
local.publisher.place | ST ALBAN-ANLAGE 66, CH-4052 BASEL, SWITZERLAND | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
local.bibliographicCitation.artnr | 1408 | - |
dc.identifier.doi | 10.3390/jcm12041408 | - |
dc.identifier.pmid | 36835942 | - |
dc.identifier.isi | 000944960400001 | - |
dc.contributor.orcid | De Boever, Patrick/0000-0002-5197-8215; Stalmans, | - |
dc.contributor.orcid | Ingeborg/0000-0001-7507-4512 | - |
local.provider.type | wosris | - |
local.description.affiliation | [Peeters, Freya; Stalmans, Ingeborg; Jacob, Julie] Univ Hosp Leuven, Dept Ophthalmol, B-3000 Leuven, Belgium. | - |
local.description.affiliation | [Peeters, Freya; Stalmans, Ingeborg; Jacob, Julie] Katholieke Univ Leuven, Dept Neurosci, Biomed Sci Grp, Res Grp Ophthalmol, B-3000 Leuven, Belgium. | - |
local.description.affiliation | [Rommes, Stef] MONA Hlth, B-3060 Bertem, Belgium. | - |
local.description.affiliation | [Rommes, Stef; Elen, Bart; Gerrits, Nele; De Boever, Patrick] Flemish Inst Technol Res VITO, B-2400 Mol, Belgium. | - |
local.description.affiliation | [De Boever, Patrick] Hasselt Univ, Ctr Environm Sci, B-3500 Hasselt, Belgium. | - |
local.description.affiliation | [Gerrits, Nele] Interuniv Microelect Ctr VZW IMEC, B-3001 Leuven, Belgium. | - |
local.uhasselt.international | no | - |
item.fulltext | With Fulltext | - |
item.accessRights | Open Access | - |
item.fullcitation | Peeters, Freya; Rommes, Stef; Elen, Bart; Gerrits, Nele; Stalmans, Ingeborg; Jacob, Julie & DE BOEVER, Patrick (2023) Artificial Intelligence Software for Diabetic Eye Screening: Diagnostic Performance and Impact of Stratification. In: Journal of Clinical Medicine, 12 (4) (Art N° 1408). | - |
item.contributor | Peeters, Freya | - |
item.contributor | Rommes, Stef | - |
item.contributor | Elen, Bart | - |
item.contributor | Gerrits, Nele | - |
item.contributor | Stalmans, Ingeborg | - |
item.contributor | Jacob, Julie | - |
item.contributor | DE BOEVER, Patrick | - |
crisitem.journal.eissn | 2077-0383 | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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Artificial Intelligence Software for Diabetic Eye Screening_ Diagnostic Performance and Impact of Stratification.pdf | Published version | 5.69 MB | Adobe PDF | View/Open |
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