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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI)
Ichhpujani, Parul
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Computer Science & IT Electrical & Electronics Engineering

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Eidos System Prediction of Myopia in Children in Early Education Stages Al-Ansi, Abdullah M.; Almadi, Mudar; Ichhpujani, Parul; Ryabtsev, Vladimir
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 2 (2023): June
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i2.26292

Abstract

This study used a database containing factors that, when processed using the Eidos intellectual system, detect myopia in children of primary school age. The database includes parameters that take into account the properties of the visual system, as well as factors that determine the duration of the performance of the main functions of the cognitive and entertaining nature of the students. The results obtained allow us to determine those factors that are more conducive to the appearance of myopia. The negative impact of some factors that cause myopia can be removed, such as, limiting the screen time spent, increasing outdoor activities/sports. A retrospective training sample can be used for automated processing using the Eidos intellectual system of the results obtained during the preventive examination of schoolchildren by an ophthalmologist. Early intervention towards myopia management in students, improves the chances of maintaining vision and slows myopia progression. The contribution of this research includes factors of a social nature that could be influenced at school in the process of education, increasing the attention towards childent, awareness of maintaining vision and slows down the progression of myopia.
Intellectual System Diagnostics Glaucoma Ichhpujani, Parul; Ryabtsev, Vladimir; Utkina, Tetyana Yuriyivna
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 4 (2023): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i4.26969

Abstract

Glaucoma is a chronic eye disease that can lead to permanent vision loss. However, glaucoma is a difficult disease to diagnose because there is no pattern in the distribution of nerve fibers in the ocular fundus. Spectral analysis of the ocular fundus images was performed using the Eidos intelligent system. From the ACRIMA eye image database, 90.7% of healthy eye images were recognized with an average similarity score of 0.588 and 74.42% of glaucoma eye images with an average similarity score of 0.558. The reliability of eye image recognition can be achieved by increasing the number of digitized parameters of eye images obtained, for example, by optical coherence tomography. The research contribution is the digital processing of fundus graphic images by the intelligent system “Eidos”. The scientific contribution lies in the automation of the glaucoma diagnosis process using digitized data. The results of the study can be used at medical faculties of universities to carry out automated diagnostics of glaucoma.
Co-Authors Al-Ansi, Abdullah M. Almadi, Mudar Ryabtsev, Vladimir Utkina, Tetyana Yuriyivna