{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,19]],"date-time":"2025-12-19T22:04:16Z","timestamp":1766181856611,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T00:00:00Z","timestamp":1648684800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","doi-asserted-by":"publisher","award":["LA\/P\/0063\/2020","UIDB\/50008\/2020"],"award-info":[{"award-number":["LA\/P\/0063\/2020","UIDB\/50008\/2020"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Medicina"],"abstract":"<jats:p>Nowadays, Artificial Intelligence (AI) and its subfields, Machine Learning (ML) and Deep Learning (DL), are used for a variety of medical applications. It can help clinicians track the patient\u2019s illness cycle, assist with diagnosis, and offer appropriate therapy alternatives. Each approach employed may address one or more AI problems, such as segmentation, prediction, recognition, classification, and regression. However, the amount of AI-featured research on Inherited Retinal Diseases (IRDs) is currently limited. Thus, this study aims to examine artificial intelligence approaches used in managing Inherited Retinal Disorders, from diagnosis to treatment. A total of 20,906 articles were identified using the Natural Language Processing (NLP) method from the IEEE Xplore, Springer, Elsevier, MDPI, and PubMed databases, and papers submitted from 2010 to 30 October 2021 are included in this systematic review. The resultant study demonstrates the AI approaches utilized on images from different IRD patient categories and the most utilized AI architectures and models with their imaging modalities, identifying the main benefits and challenges of using such methods.<\/jats:p>","DOI":"10.3390\/medicina58040504","type":"journal-article","created":{"date-parts":[[2022,3,31]],"date-time":"2022-03-31T21:34:29Z","timestamp":1648762469000},"page":"504","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["A Systematic Review of Artificial Intelligence Applications Used for Inherited Retinal Disease Management"],"prefix":"10.3390","volume":"58","author":[{"given":"Meltem","family":"Eseng\u00f6n\u00fcl","sequence":"first","affiliation":[{"name":"Escola de Ci\u00eancias e Tecnologia, University of Tr\u00e1s-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal"},{"name":"Department of Life Sciences Engineering, University of Applied Sciences Technikum Wien, 1200 Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3495-4649","authenticated-orcid":false,"given":"Ana","family":"Marta","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, Porto University Hospital Center, 4099-001 Porto, Portugal"},{"name":"Abel Salazar Biomedical Sciences Institute, University of Porto, 4050-313 Porto, Portugal"}]},{"given":"Jo\u00e3o","family":"Beir\u00e3o","sequence":"additional","affiliation":[{"name":"Department of Ophthalmology, Porto University Hospital Center, 4099-001 Porto, Portugal"},{"name":"Abel Salazar Biomedical Sciences Institute, University of Porto, 4050-313 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3394-6762","authenticated-orcid":false,"given":"Ivan Miguel","family":"Pires","sequence":"additional","affiliation":[{"name":"Escola de Ci\u00eancias e Tecnologia, University of Tr\u00e1s-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal"},{"name":"Instituto de Telecomunica\u00e7\u00f5es, Universidade da Beira Interior, 6200-001 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3458-7693","authenticated-orcid":false,"given":"Ant\u00f3nio","family":"Cunha","sequence":"additional","affiliation":[{"name":"Escola de Ci\u00eancias e Tecnologia, University of Tr\u00e1s-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal"},{"name":"Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ci\u00eancia, 3200-465 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1007\/978-3-030-27378-1_12","article-title":"RNA-Based Therapeutic Strategies for Inherited Retinal Dystrophies","volume":"1185","author":"Garanto","year":"2019","journal-title":"Adv. Exp. Med. Biol."},{"key":"ref_2","unstructured":"(2022, March 30). Retinal Information Network. Available online: https:\/\/sph.uth.edu\/retnet\/."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2710","DOI":"10.1073\/pnas.1913179117","article-title":"Worldwide Carrier Frequency and Genetic Prevalence of Autosomal Recessive Inherited Retinal Diseases","volume":"117","author":"Hanany","year":"2020","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1016\/j.ajo.2015.06.032","article-title":"Multimodal Imaging of Central Retinal Disease Progression in a 2 Year Mean Follow up of Retinitis Pigmentosa","volume":"160","author":"Sujirakul","year":"2015","journal-title":"Am. J. Ophthalmol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1795","DOI":"10.1016\/S0140-6736(06)69740-7","article-title":"Retinitis Pigmentosa","volume":"368","author":"Hartong","year":"2006","journal-title":"Lancet"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1159\/000503294","article-title":"The Impact of Progressive Visual Field Constriction on Reading Ability in an Inherited Retinal Degeneration","volume":"243","author":"Jolly","year":"2020","journal-title":"Ophthalmologica"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"5575","DOI":"10.1167\/iovs.17-22486","article-title":"Characterizing the Natural History of Visual Function in Choroideremia Using Microperimetry and Multimodal Retinal Imaging","volume":"58","author":"Jolly","year":"2017","journal-title":"Investig. Ophthalmol. Vis. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1167\/tvst.5.2.6","article-title":"Correlating Photoreceptor Mosaic Structure to Clinical Findings in Stargardt Disease","volume":"5","author":"Razeen","year":"2016","journal-title":"Transl. Vis. Sci. Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1016\/0002-9394(88)90309-1","article-title":"Bilateral Macular Holes after Nd:YAG Laser Posterior Capsulotomy","volume":"105","author":"Blacharski","year":"1988","journal-title":"Am. J. Ophthalmol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.spen.2019.05.006","article-title":"The Assessment of Visual Function and Functional Vision","volume":"31","author":"Bennett","year":"2019","journal-title":"Semin. Pediatr. Neurol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1007\/978-3-319-95046-4_5","article-title":"Electroretinography","volume":"1085","author":"Tsang","year":"2018","journal-title":"Adv. Exp. Med. Biol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1016\/B978-0-444-64032-1.00033-3","article-title":"The Electrooculogram","volume":"160","author":"Creel","year":"2019","journal-title":"Handb. Clin. Neurol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1055\/a-1388-7236","article-title":"Diagnosis of Inherited Retinal Diseases","volume":"238","author":"Birtel","year":"2021","journal-title":"Klin. Monbl. Augenheilkd."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1109\/RBME.2010.2084567","article-title":"Retinal Imaging and Image Analysis","volume":"3","author":"Garvin","year":"2010","journal-title":"IEEE Rev. Biomed. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1097\/ICU.0b013e32835f8bf8","article-title":"Optical Coherence Tomography\u2014Current and Future Applications","volume":"24","year":"2013","journal-title":"Curr. Opin. Ophthalmol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"995","DOI":"10.1038\/eye.2017.19","article-title":"Fundus Autofluorescence Imaging: Systematic Review of Test Accuracy for the Diagnosis and Monitoring of Retinal Conditions","volume":"31","author":"Frampton","year":"2017","journal-title":"Eye"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"252","DOI":"10.1111\/aos.13247","article-title":"Reduced Metabolic Function and Structural Alterations in Inherited Retinal Dystrophies: Investigating the Effect of Peripapillary Vessel Oxygen Saturation and Vascular Diameter on the Retinal Nerve Fibre Layer Thickness","volume":"95","author":"Bojinova","year":"2017","journal-title":"Acta Ophthalmol."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"518170","DOI":"10.1155\/2013\/518170","article-title":"Photoreceptor Impairment and Restoration on Optical Coherence Tomographic Image","volume":"2013","author":"Mitamura","year":"2013","journal-title":"J. Ophthalmol."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1097\/IAE.0b013e31821a891a","article-title":"Evaluation of Retinal Nerve Fiber Layer Thickness in Patients with Retinitis Pigmentosa Using Spectral-Domain Optical Coherence Tomography","volume":"32","author":"Anastasakis","year":"2012","journal-title":"Retina"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1159\/000337227","article-title":"Retinal Nerve Fiber Layer Analysis with Scanning Laser Polarimetry and RTVue-OCT in Patients of Retinitis Pigmentosa","volume":"229","author":"Xue","year":"2013","journal-title":"Ophthalmologica"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1007\/978-3-319-17121-0_41","article-title":"Wide-Field Fundus Autofluorescence for Retinitis Pigmentosa and Cone\/Cone-Rod Dystrophy","volume":"854","author":"Oishi","year":"2016","journal-title":"Adv. Exp. Med. Biol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1007\/978-3-030-27378-1_43","article-title":"Emerging Drug Therapies for Inherited Retinal Dystrophies","volume":"1185","author":"Sundaramurthi","year":"2019","journal-title":"Adv. Exp. Med. Biol."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"(2022). Early and Late Stage Gene Therapy Interventions for Inherited Retinal Degenerations. Prog. Retin. Eye Res., 86, 100975.","DOI":"10.1016\/j.preteyeres.2021.100975"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"657","DOI":"10.14245\/ns.1938396.198","article-title":"Deep Learning in Medical Imaging","volume":"16","author":"Kim","year":"2019","journal-title":"Neurospine"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1126\/science.aaa8415","article-title":"Machine Learning: Trends, Perspectives, and Prospects","volume":"349","author":"Jordan","year":"2015","journal-title":"Science"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep Learning","volume":"521","author":"LeCun","year":"2015","journal-title":"Nature"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Zdravevski, E., Lameski, P., Trajkovik, V., Chorbev, I., Goleva, R., Pombo, N., and Garcia, N.M. (2019). Automation in Systematic, Scoping and Rapid Reviews by an NLP Toolkit: A Case Study in Enhanced Living Environments. Enhanced Living Environments, Springer.","DOI":"10.1007\/978-3-030-10752-9_1"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"3092","DOI":"10.1364\/BOE.9.003092","article-title":"Deep Learning for the Segmentation of Preserved Photoreceptors on En Face Optical Coherence Tomography in Two Inherited Retinal Diseases","volume":"9","author":"Camino","year":"2018","journal-title":"Biomed. Opt. Express"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"7911","DOI":"10.1038\/s41598-018-26350-3","article-title":"Automatic Cone Photoreceptor Localisation in Healthy and Stargardt Afflicted Retinas Using Deep Learning","volume":"8","author":"Davidson","year":"2018","journal-title":"Sci. Rep."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"e201700313","DOI":"10.1002\/jbio.201700313","article-title":"Automated Detection of Preserved Photoreceptor on Optical Coherence Tomography in Choroideremia Based on Machine Learning","volume":"11","author":"Wang","year":"2018","journal-title":"J. Biophotonics"},{"key":"ref_31","first-page":"1691064","article-title":"Japan Eye Genetics Consortium OBO Prediction of Causative Genes in Inherited Retinal Disorders from Spectral-Domain Optical Coherence Tomography Utilizing Deep Learning Techniques","volume":"2019","author":"Pontikos","year":"2019","journal-title":"J. Ophthalmol."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"16491","DOI":"10.1038\/s41598-020-73339-y","article-title":"Deep Learning Segmentation of Hyperautofluorescent Fleck Lesions in Stargardt Disease","volume":"10","author":"Charng","year":"2020","journal-title":"Sci. Rep."},{"key":"ref_33","unstructured":"(2022, February 08). Automatic Detection of Genetic Diseases in Pediatric Age Using Pupillometry. Available online: https:\/\/ieeexplore.ieee.org\/document\/8998205."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Miere, A., Le Meur, T., Bitton, K., Pallone, C., Semoun, O., Capuano, V., Colantuono, D., Taibouni, K., Chenoune, Y., and Astroz, P. (2020). Deep Learning-Based Classification of Inherited Retinal Diseases Using Fundus Autofluorescence. J. Clin. Med. Res., 9.","DOI":"10.3390\/jcm9103303"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"e715","DOI":"10.1111\/aos.14353","article-title":"Automated Classification of Normal and Stargardt Disease Optical Coherence Tomography Images Using Deep Learning","volume":"98","author":"Shah","year":"2020","journal-title":"Acta Ophthalmol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"800","DOI":"10.3389\/fnins.2020.00800","article-title":"Foveal Therapy in Blue Cone Monochromacy: Predictions of Visual Potential From Artificial Intelligence","volume":"14","author":"Sumaroka","year":"2020","journal-title":"Front. Neurosci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"948","DOI":"10.1007\/s10278-021-00479-6","article-title":"Artificial Intelligence-Assisted Early Detection of Retinitis Pigmentosa\u2014The Most Common Inherited Retinal Degeneration","volume":"34","author":"Chen","year":"2021","journal-title":"J. Digit. Imaging"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"104198","DOI":"10.1016\/j.compbiomed.2020.104198","article-title":"Deep Learning-Based Classification of Retinal Atrophy Using Fundus Autofluorescence Imaging","volume":"130","author":"Miere","year":"2021","journal-title":"Comput. Biol. Med."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"n71","DOI":"10.1136\/bmj.n71","article-title":"The PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews","volume":"372","author":"Page","year":"2021","journal-title":"BMJ"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2278","DOI":"10.1109\/5.726791","article-title":"Gradient-Based Learning Applied to Document Recognition","volume":"86","author":"Lecun","year":"1998","journal-title":"Proc. IEEE"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Karbhari, V.M., and Ansari, F. (2009). Synthetic Aperture Radar and Remote Sensing Technologies for Structural Health Monitoring of Civil Infrastructure Systems. Structural Health Monitoring of Civil Infrastructure Systems, Woodhead Publishing.","DOI":"10.1533\/9781845696825"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Ongsulee, P., Chotchaung, V., Bamrungsi, E., and Rodcheewit, T. (2018, January 21\u201323). Big Data, Predictive Analytics and Machine Learning. Proceedings of the 2018 16th International Conference on ICT and Knowledge Engineering (ICT KE), Bangkok, Thailand.","DOI":"10.1109\/ICTKE.2018.8612393"},{"key":"ref_43","unstructured":"(2022, February 10). Object Recognition. Available online: https:\/\/www.mathworks.com\/solutions\/image-video-processing\/object-recognition.html."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Musulin, J., Baressi \u0160egota, S., \u0160tifani\u0107, D., Lorencin, I., An\u0111eli\u0107, N., \u0160u\u0161ter\u0161i\u010d, T., Blagojevi\u0107, A., Filipovi\u0107, N., \u0106abov, T., and Markova-Car, E. (2021). Application of Artificial Intelligence-Based Regression Methods in the Problem of COVID-19 Spread Prediction: A Systematic Review. Int. J. Environ. Res. Public Health, 18.","DOI":"10.3390\/ijerph18084287"},{"key":"ref_45","unstructured":"(2022, February 10). Semantic Segmentation. Available online: https:\/\/www.mathworks.com\/solutions\/image-video-processing\/semantic-segmentation.html."}],"container-title":["Medicina"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1648-9144\/58\/4\/504\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:47:42Z","timestamp":1760136462000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1648-9144\/58\/4\/504"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,31]]},"references-count":45,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["medicina58040504"],"URL":"https:\/\/doi.org\/10.3390\/medicina58040504","relation":{},"ISSN":["1648-9144"],"issn-type":[{"type":"electronic","value":"1648-9144"}],"subject":[],"published":{"date-parts":[[2022,3,31]]}}}