Prediction of Myopia Progression Based on Artificial Intelligence Model

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Published Sep 14, 2021
Sivakumar Rajagopal Subhalaxmi Swain

Abstract

Myopia is a leading socio-economical issue that gives a threat mostly to the pediatric population. This issue can lead to visual impairment as well if the prediction and prevention are not done properly. According to the World Health Organization (WHO) around 27% of people all over the world’s population are suffering from myopia. By considering the population of the united nation maximum of 52% of the population is suffering from myopia. Considering the pediatric population maximum of 80%-90% of the population is suffering from different stages of myopia [1-3]. The increasing rate of myopia is having a distinct amount of reason behind it. As children are more prone to this visual error, time spent on the electronic system (TV, smartphone) and for studying, reading can also be one important cause of myopia. Also, some genetic and environmental factors can be considered as one of the cause. According to many types of research in ophthalmology, the field shows that the structural changes in a visual component can also lead to myopia. If the cornea is a little more curved than the normal eye then, the light ray focused incorrectly which leads to myopia [4-5]. This paper proposes a prediction of myopia progression based on Artificial Intelligence (AI)gives an idea about myopia which becomes a leading health concern and socio-economical issue with a big threat to the pediatric population. Also, give an idea about some genetic and environmental factors for myopia progression. Clinical, environmental markers are used for predicting this visually threatening disease. Involvement of corneal biomechanics, a different mode of managing myopia, most important, different approaches for predicting myopia, and an efficient model selection for handling such huge data from EMR and predicting the disease perfectly with the help of AI[fig.1]. we conclude that myopia is a very serious socio-economical issue and recently became the leading public health problem mostly a threat to the pediatric population. In recent days huge medical record AI is a boon to medical science. With the help of an efficient AI model, it is possible to predict myopia with greater efficacy than manual prediction.   

How to Cite

Rajagopal, S., & Subhalaxmi Swain. (2021). Prediction of Myopia Progression Based on Artificial Intelligence Model . SPAST Abstracts, 1(01). Retrieved from https://spast.org/techrep/article/view/299
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References
[1] Brien Holden, “Vision Institute Global Scientific Meeting on Myopia”, World Health Organization,2015.
[2] Andrzej Grzybowski et.al. “A review on the epidemiology of myopia in school children worldwide”, BMC Ophthalmology,2020
[3] Daniel Ian Flitcroft, “IMI – Defining and Classifying Myopia: A Proposed Set of Standards for Clinical and Epidemiologic Studies”, Investigative Ophthalmology& Visual Science, Vol.60, issue 3, pp. M20-M30,2019
[4] A-Yong Yu, et.al. “Corneal biomechanical properties in myopic eyes evaluated via Scheimpflug imaging”, BMC Ophthalmology, Vol.20, pp. 1-7, 2020.
[5]Christos Theophanou et.al. “Myopia prevalence and risk factors in children”, Clinical Ophthalmology, Vol.12, pp. 1581-1587, 2018.
Section
GE3- Computers & Information Technology

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