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Status: Bibliographieeintrag

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Verfasst von:Müller, Philipp Lothar [VerfasserIn]   i
 Treis, Tim [VerfasserIn]   i
 Odainic, Alexandru [VerfasserIn]   i
 Pfau, Maximilian [VerfasserIn]   i
 Herrmann, Philipp [VerfasserIn]   i
 Tufail, Adnan [VerfasserIn]   i
 Holz, Frank G. [VerfasserIn]   i
Titel:Prediction of function in ABCA4-related retinopathy using ensemble machine learning
Verf.angabe:Philipp L. Müller, Tim Treis, Alexandru Odainic, Maximilian Pfau, Philipp Herrmann, Adnan Tufail and Frank G. Holz
E-Jahr:2020
Jahr:29 July 2020
Umfang:15 S.
Fussnoten:Gesehen am 22.10.2020
Titel Quelle:Enthalten in: Journal of Clinical Medicine
Ort Quelle:Basel : MDPI, 2012
Jahr Quelle:2020
Band/Heft Quelle:9(2020,8) Artikel-Nummer 2428, 15 Seiten
ISSN Quelle:2077-0383
Abstract:Full-field electroretinogram (ERG) and best corrected visual acuity (BCVA) measures have been shown to have prognostic value for recessive Stargardt disease (also called “ABCA4-related retinopathy”). These functional tests may serve as a performance-outcome-measure (PerfO) in emerging interventional clinical trials, but utility is limited by variability and patient burden. To address these limitations, an ensemble machine-learning-based approach was evaluated to differentiate patients from controls, and predict disease categories depending on ERG (‘inferred ERG’) and visual impairment (‘inferred visual impairment’) as well as BCVA values (‘inferred BCVA’) based on microstructural imaging (utilizing spectral-domain optical coherence tomography) and patient data. The accuracy for ‘inferred ERG’ and ‘inferred visual impairment’ was up to 99.53 ± 1.02%. Prediction of BCVA values (‘inferred BCVA’) achieved a precision of ±0.3LogMAR in up to 85.31% of eyes. Analysis of the permutation importance revealed that foveal status was the most important feature for BCVA prediction, while the thickness of outer nuclear layer and photoreceptor inner and outer segments as well as age of onset highly ranked for all predictions. ‘Inferred ERG’, ‘inferred visual impairment’, and ‘inferred BCVA’, herein, represent accurate estimates of differential functional effects of retinal microstructure, and offer quasi-functional parameters with the potential for a refined patient assessment, and investigation of potential future treatment effects or disease progression.
DOI:doi:10.3390/jcm9082428
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext ; Verlag: https://doi.org/10.3390/jcm9082428
 Volltext: https://www.mdpi.com/2077-0383/9/8/2428
 DOI: https://doi.org/10.3390/jcm9082428
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:artificial intelligence
 electroretinogram
 hereditary retinal disease
 optical coherence tomography
 retina
 Stargardt disease
 visual acuity
K10plus-PPN:1736236628
Verknüpfungen:→ Zeitschrift

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