Machine Learning Applications in Pediatric Ophthalmology
Purpose: To describe emerging applications of machine learning (ML) in pediatric ophthalmology with an emphasis on the diagnosis and treatment of disorders affecting visual development. Methods: Literature review of studies applying ML algorithms to problems in pediatric ophthalmology. Results: At present, the ML literature emphasizes applications in retinopathy of prematurity. However, there are increasing efforts to apply ML techniques in the diagnosis of amblyogenic conditions such as pediatric cataracts, strabismus, and high refractive error. Conclusions: A greater understanding of the principles governing ML will enable pediatric eye care providers to apply the methodology to unexplored challenges within the subspecialty.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:36 |
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| Enthalten in: |
Seminars in ophthalmology - 36(2021), 4 vom: 19. Mai, Seite 210-217 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Oke, Isdin [VerfasserIn] |
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| Links: |
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| Themen: |
Artificial intelligence |
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| Anmerkungen: |
Date Completed 28.10.2021 Date Revised 31.05.2022 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1080/08820538.2021.1890151 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM321994884 |
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| 520 | |a Purpose: To describe emerging applications of machine learning (ML) in pediatric ophthalmology with an emphasis on the diagnosis and treatment of disorders affecting visual development. Methods: Literature review of studies applying ML algorithms to problems in pediatric ophthalmology. Results: At present, the ML literature emphasizes applications in retinopathy of prematurity. However, there are increasing efforts to apply ML techniques in the diagnosis of amblyogenic conditions such as pediatric cataracts, strabismus, and high refractive error. Conclusions: A greater understanding of the principles governing ML will enable pediatric eye care providers to apply the methodology to unexplored challenges within the subspecialty | ||
| 650 | 4 | |a Journal Article | |
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