Machine Learning and Deep Learning Techniques Features and Obstacles in the Cataract Diagnosis

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Abstract

Cataract is a degenerative condition that, according to estimations, will rise globally. Even though there are various proposals about its diagnosis, there are remaining problems to be solved. This paper aims to identify the current situation of the recent investigations on cataract diagnosis using a framework to conduct the literature review with the intention of answering the following research questions: RQ1) Which are the existing methods for cataract diagnosis? RQ2) Which are the features considered for the diagnosis of cataracts? RQ3) Which is the existing classification when diagnosing cataracts? RQ4) And Which obstacles arise when diagnosing cataracts? Additionally, a cross-analysis of the results was made. The results showed that new research is required in: (1) the classification of “congenital cataract” and, (2) portable solutions, which are necessary to make cataract diagnoses easily and at a low cost.

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Ñuflo, I., Mecca, F., & Wong, L. (2020). Machine Learning and Deep Learning Techniques Features and Obstacles in the Cataract Diagnosis. International Journal of Recent Technology and Engineering (IJRTE), 9(3), 87–92. https://doi.org/10.35940/ijrte.c4283.099320

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