Eye Disease Prediction Among Corporate Employees using Machine Learning Techniques
A. Tamilarasi1, T. Jawahar Karthick2, R. Dharani3, S. Jeevitha4
1Dr. A. Tamilarasi, Professor, Department of Computer Applications, Kongu Engineering College, Perundurai-638060, (Tamilnadu), India.
2T. Jawahar Karthick, PG Final Year, Department of Computer Applications, Kongu Engineering College, Perundurai-638060, (Tamilnadu), India.
3R. Dharani, PG Final Year, Department of Computer Applications, Kongu Engineering College, Perundurai-638060, (Tamilnadu), India.
4S. Jeevitha, PG Final Year, Department of Computer Applications, Kongu Engineering College, Perundurai-638060, (Tamilnadu), India.
Manuscript received on 11 August 2023 | Revised Manuscript received on 13 September 2023 | Manuscript Accepted on 15 September 2023 | Manuscript published on 30 September 2023 | PP: 1-5 | Volume-11 Issue-10, September 2023 | Retrieval Number: 100.1/ijese.C78950912323 | DOI: 10.35940/ijese.C7895.09111023
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the IT sector, employees use systems for more than six hs, so they are affected by many health problems. In the IT sector, employees are often affected by eye-related issues, including eye strain, eye pain, a burning sensation, double vision, blurred vision, and frequent eye watering. The primary goal of this research is to identify the various types of eye problems encountered, the symptoms present, and the population affected by eye diseases, to forecast outcomes using machine learning techniques for real-time datasets accurately.
Keywords: Machine Learning Techniques
Scope of the Article: Machine Learning