Machine learning in ocular oncology and oculoplasty: Transforming diagnosis and treatment


Review Article

Author Details : Dipali Vikas Mane*, Pankaj Ramdas Khuspe

Volume : 10, Issue : 4, Year : 2024

Article Page : 196-207

https://doi.org/10.18231/j.ijooo.2024.036



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Abstract

In the domains of ocular oncology and oculoplasty, machine learning (ML) has become a game-changing technology, providing previously unheard-of levels of precision in diagnosis, treatment planning, and outcome prediction. Using imaging modalities, genomic data, and clinical characteristics, this chapter investigates the integration of machine learning algorithms in the detection and treatment of ocular tumours, including retinoblastoma and uveal melanoma. Through predictive modelling and real-time decision-making, it also emphasises how ML might improve surgical outcomes in oculoplasty, including orbital reconstruction and eyelid correction. Automated examination of fundus photographs, histological slides, and 3D imaging has been made possible by methods like deep learning and natural language processing, which have improved individualised therapeutic approaches and decreased diagnostic errors. Additionally, the use of augmented reality and machine learning in robotics and surgery is a significant development in precision oculoplasty. Notwithstanding its potential, issues including data heterogeneity, algorithm interpretability, and ethical considerations are significant roadblocks that need to be addressed. This chapter explores cutting-edge developments, real-world uses, and potential future paths, offering researchers and doctors a thorough resource.Dipali Vikas Mane, Associate Professor, Shriram Shikshan Sanstha’s College of Pharmacy, Paniv-413113
 

Keywords: Machine learning, Ocularoncology, Oculoplasty, Deep learning, Personalized medicine


How to cite : Mane D V, Khuspe P R, Machine learning in ocular oncology and oculoplasty: Transforming diagnosis and treatment. IP Int J Ocul Oncol Oculoplasty 2024;10(4):196-207


This is an Open Access (OA) journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.







Article History

Received : 03-11-2024

Accepted : 23-12-2024


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https://doi.org/ 10.18231/j.ijooo.2024.036


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