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Seminars in Ophthalmology Volume 34, 2019 - Issue 1
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Introduction to Machine Learning for Ophthalmologists

Alejandra ConsejoDepartment of Ophthalmology, Antwerp University Hospital, Edegem, Belgium;Department of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium;Department of Biomedical Engineering, Wroclaw University of Science and Technology, Wroclaw, Poland;Institute of Physical Chemistry, Polish Academy of Sciences, Warsaw, PolandCorrespondence[email protected]
ORCID Iconhttps://orcid.org/0000-0001-5186-1837View further author information
ORCID Icon,
Tomasz MelcerDepartment of Biomedical Engineering, Wroclaw University of Science and Technology, Wroclaw, PolandView further author information
&
Jos J. RozemaDepartment of Ophthalmology, Antwerp University Hospital, Edegem, Belgium;Department of Medicine and Health Sciences, University of Antwerp, Antwerp, BelgiumView further author information
Pages 19-41 | Received 11 Dec 2017, Accepted 15 Nov 2018, Published online: 30 Nov 2018

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Ronald Cheung, Samantha So & Monali S. Malvankar-Mehta. (2022) Diagnostic accuracy of machine learning classifiers for cataracts: a systematic review and meta-analysis. Expert Review of Ophthalmology 17:6, pages 427-437.
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Dan Gong, Ashley Kras & John B Miller. (2021) Application of Deep Learning for Diagnosing, Classifying, and Treating Age-Related Macular Degeneration. Seminars in Ophthalmology 36:4, pages 198-204.
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Renato Ambrósio$suffix/text()$suffix/text(). (2019) Post-LASIK Ectasia: Twenty Years of a Conundrum. Seminars in Ophthalmology 34:2, pages 66-68.
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Articles from other publishers (19)

Myron Yanoff & Joseph W. Sassani. 2025. Ocular Pathology. Ocular Pathology 1 53.e13 .
Izabela K. Garaszczuk, Maria Romanos‐Ibanez & Alejandra Consejo. (2024) Machine learning‐based prediction of tear osmolarity for contact lens practice. Ophthalmic and Physiological Optics 44:4, pages 727-736.
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Tzu-En Wu, Jun-Wei Chen, Tzu-Chi Liu, Chieh-Han Yu, Mao-Jhen Jhou & Chi-Jie Lu. (2024) Identifying and Exploring the Impact Factors for Intraocular Pressure Prediction in Myopic Children with Atropine Control Utilizing Multivariate Adaptive Regression Splines. Journal of Personalized Medicine 14:1, pages 125.
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Savita R. Gandhi, Jigna Satani, Kashyap Jadav & Arshil Shah. (2023) Detection of Keratoconus and Forme Fruste Keratoconus Through Supervised Machine Learning Algorithms. Detection of Keratoconus and Forme Fruste Keratoconus Through Supervised Machine Learning Algorithms.
Esmaeil Shakeri, Trafford Crump, Ezekiel Weis, Emad Mohammed, Roberto Souza & Behrouz Far. (2023) Explaining Eye Diseases Detected by Machine Learning Using SHAP: A Case Study of Diabetic Retinopathy and Choroidal Nevus. SN Computer Science 4:5.
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Anupam Singh. (2023) Artificial intelligence applications for pediatric ophthalmology; a long way to go. Himalayan Journal of Ophthalmology 17:2, pages 29.
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Savita R. Gandhi, Jigna Satani & Dax Jain. 2023. ICT with Intelligent Applications. ICT with Intelligent Applications 165 178 .
He-Bei GaoZhi-Geng PanMei-Xiao Shen, Fan Lu, Hong LiXiao-Qin Zhang. (2022) KeratoScreen: Early Keratoconus Classification With Zernike Polynomial Using Deep Learning. Cornea 41:9, pages 1158-1165.
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Shi-Ming Li, Ming-Yang Ren, Jiahe Gan, San-Guo Zhang, Meng-Tian Kang, He Li, David A. Atchison, Jos Rozema, Andrzej Grzybowski & Ningli Wang. (2022) Machine Learning to Determine Risk Factors for Myopia Progression in Primary School Children: The Anyang Childhood Eye Study. Ophthalmology and Therapy 11:2, pages 573-585.
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K. Harrison, H. Pullen, C. Welsh, O. Oktay, J. Alvarez-Valle & R. Jena. (2022) Machine Learning for Auto-Segmentation in Radiotherapy Planning. Clinical Oncology 34:2, pages 74-88.
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Clifford B. Kim & Grayson W. Armstrong. (2022) Characterizing Infectious Keratitis Using Artificial Intelligence. International Ophthalmology Clinics 62:2, pages 41-53.
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Andrés García-Jiménez & Alejandra Consejo. (2022) Suspect glaucoma detection from corneal densitometry supported by machine learning. Journal of Optometry 15, pages S12-S21.
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Savita R. Gandhi, Jigna Satani, Karan Bhuva & Parth Patadiya. 2021. Computer Vision and Image Processing. Computer Vision and Image Processing 367 380 .
Renu Vadhera & Meghna Sharma. 2021. Proceedings of the Second International Conference on Information Management and Machine Intelligence. Proceedings of the Second International Conference on Information Management and Machine Intelligence 191 201 .
Ikram Issarti & Jos J. Rozema. 2021. Artificial Intelligence in Ophthalmology. Artificial Intelligence in Ophthalmology 17 30 .
Lucas Lo Vercio, Kimberly Amador, Jordan J Bannister, Sebastian Crites, Alejandro Gutierrez, M. Ethan MacDonald, Jasmine Moore, Pauline Mouches, Deepthi Rajashekar, Serena Schimert, Nagesh Subbanna, Anup Tuladhar, Nanjia Wang, Matthias Wilms, Anthony Winder & Nils D Forkert. (2020) Supervised machine learning tools: a tutorial for clinicians. Journal of Neural Engineering 17:6, pages 062001.
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Alejandra Consejo, Jedrzej Solarski, Karol Karnowski, Jos J Rozema, Maciej Wojtkowski & D. Robert Iskander. (2020) Keratoconus Detection Based on a Single Scheimpflug Image. Translational Vision Science & Technology 9:7, pages 36.
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Sang Min Nam, Thomas A Peterson, Atul J Butte, Kyoung Yul Seo & Hyun Wook Han. (2020) Explanatory Model of Dry Eye Disease Using Health and Nutrition Examinations: Machine Learning and Network-Based Factor Analysis From a National Survey. JMIR Medical Informatics 8:2, pages e16153.
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Julia E. Reid & Eric Eaton. (2019) Artificial intelligence for pediatric ophthalmology. Current Opinion in Ophthalmology 30:5, pages 337-346.
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