دورية أكاديمية

Essentials of a Robust Deep Learning System for Diabetic Retinopathy Screening: A Systematic Literature Review

التفاصيل البيبلوغرافية
العنوان: Essentials of a Robust Deep Learning System for Diabetic Retinopathy Screening: A Systematic Literature Review
المؤلفون: Aan Chu, David Squirrell, Andelka M. Phillips, Ehsan Vaghefi
المصدر: Journal of Ophthalmology, Vol 2020 (2020)
بيانات النشر: Hindawi Limited, 2020.
سنة النشر: 2020
المجموعة: LCC:Ophthalmology
مصطلحات موضوعية: Ophthalmology, RE1-994
الوصف: This systematic review was performed to identify the specifics of an optimal diabetic retinopathy deep learning algorithm, by identifying the best exemplar research studies of the field, whilst highlighting potential barriers to clinical implementation of such an algorithm. Searching five electronic databases (Embase, MEDLINE, Scopus, PubMed, and the Cochrane Library) returned 747 unique records on 20 December 2019. Predetermined inclusion and exclusion criteria were applied to the search results, resulting in 15 highest-quality publications. A manual search through the reference lists of relevant review articles found from the database search was conducted, yielding no additional records. A validation dataset of the trained deep learning algorithms was used for creating a set of optimal properties for an ideal diabetic retinopathy classification algorithm. Potential limitations to the clinical implementation of such systems were identified as lack of generalizability, limited screening scope, and data sovereignty issues. It is concluded that deep learning algorithms in the context of diabetic retinopathy screening have reported impressive results. Despite this, the potential sources of limitations in such systems must be evaluated carefully. An ideal deep learning algorithm should be clinic-, clinician-, and camera-agnostic; complying with the local regulation for data sovereignty, storage, privacy, and reporting; whilst requiring minimum human input.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2090-004X
2090-0058
العلاقة: https://doaj.org/toc/2090-004XTest; https://doaj.org/toc/2090-0058Test
DOI: 10.1155/2020/8841927
الوصول الحر: https://doaj.org/article/d70d82b9f91e4e6ea973a5cb5e020f0bTest
رقم الانضمام: edsdoj.70d82b9f91e4e6ea973a5cb5e020f0b
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:2090004X
20900058
DOI:10.1155/2020/8841927