[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120766-en":3,"doc-seo-120766-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},120766,34359740700684,"Finn","https://ap-avatar.wpscdn.com/avatar/1f400023980c374ae676?_k=1777273430885731487",7,"Healthcare","Eye Disease Prediction Among Corporate Employees using Machine Learning Techniques","IT-sector employees often spend over 6 hours using computer systems, increasing exposure to multiple eye-related health issues such as eye strain, eye pain, burning sensation, double vision, blurred vision, and frequent watering. This research aims to identify common categories of eye problems and their symptoms, and to determine the affected population profile. Machine-learning models are used to forecast outcomes in real time using dataset bio factors, and model accuracy is evaluated and compared using Naive Bayes, SVM, and KNN.","Eye Disease Prediction Among Corporate Employees using Machine Learning Techniques  \nA. Tamilarasi, T. Jawahar Karthick, R. Dharani, S. Jeevitha   \nAbstract: In the IT sector, employees use systems for more than 6 hs, so they are a fected by many health problems. Mostly In the IT sector, employees are a fected with eye diseases like eye strain, eye pain, burning sensation, double vision, blurring of vision, and frequent watering. The major goal of this research is to identify the different types of eye problems encountered, the symptoms present, and the population aflicted by eye diseases in order to accurately forecast outcomes using a Machine learning techniques for real-time data sets.  \nKeywords: Machine Learning Techniques  \nI. INTRODUCTION  \nThe eye is the smallest and one of the most important organs in the human body. Therefore, it is crucial to take care of it. As a result, since the majority of diseases have a brain component, it is essential to anticipate ocular issues, which calls for comparative research. Since the inaccuracy of the instrument causes the majority of patients to lose their eyes nowadays, it is crucial to comprehend the most efficient ways to reduce illness risk. The testing approach that has had the most success is machine learning. In the vast field of study known as machine learning (ML), computers are taught to mimic human talents. The term \"machine intelligence,\"which describes the fusion of the two technologies, refers to machine learning systems that are taught how to analysis and utilize data. As testing data for this paper, use bio factors like  \n• Age  \n• Experience  \n• H of work  \nevaluate the accuracy with the use of the following algorithms, Naive Bayes, SVM, KNN. In this study, predict the accuracy of above three different machine learning algorithms and compare which one is the best.  \nManuscript received on 11 August 2023 | Revised Manuscript received on 13 September 2023 | Manuscript Accepted on 15 September 2023 | Manuscript published on 30 September 2023.  \n*Correspondence Author(s)  \nDr. A. Tamilarasi*, Professor, Department of Computer Applications, Kongu Engineering College, Perundurai-638060, (Tamilnadu), India. Email: [drtamil@kongu.ac.in](drtamil@kongu.ac.in), ORCID ID: 0000-0002-5885-5541  \nT. Jawahar Karthick, PG Final Year, Department of Computer Applications, Kongu Engineering College, Perundurai-638060,(Tamilnadu), India.Email: [j](jawaharkarthickt.21mca@kongu.edu)[awaharkarthickt.21mca@kongu.edu](jawaharkarthickt.21mca@kongu.edu)  \n[R](R). Dharani, PG Final Year, Department of Computer Applications, Kongu Engineering College, Perundurai-638060, (Tamilnadu), India. E[mail: ](mail: dharanir.21mca@kongu.edu)[dharanir.21mca@kongu.edu](mail: dharanir.21mca@kongu.edu)  \nS. Jeevitha, PG Final Year, Department of Computer Applications, Kongu Engineering College, Perundurai-638060, (Tamilnadu), India. E-mail:  \n[j](jeevithas.21mca@kongu.edu)[eevithas.21mca@kongu.edu](jeevithas.21mca@kongu.edu)  \n© The Authors. Published by 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/](http://creativecommons.org/licenses/by-nc-nd/4.0/)  \nThe two ideas of testing and training are the foundation of the potent instrument known as machine learning. The application of a test to various types of needs is done by a system using the information it has gained through data and experience and an algorithm. Supervised, unsupervised, and reinforced machine learning approaches are the three categories.  \nII. SUPERVISED LEARNING  \nSupervised Learning is defined as learning with the assistance of a teacher or a qualified guide. There is always a training dataset available when testing data is available since have a database that can be used to teach prediction in a specific database. \"Train me\" is the guiding premise of supervised learning. The following are the fundamental s","cbCaiihPFWfgxz7s","https://ap.wps.com/l/cbCaiihPFWfgxz7s","pdf",471347,1,5,"English","en",105,"# Introduction\n## Supervised learning\n## Unsupervised learning\n## Reinforcement learning\n# Eye problem overview\n## Red eyes","[{\"question\":\"Why focus on eye disease prediction for corporate employees?\",\"answer\":\"Employees in the IT sector spend long hours using systems, which is associated with frequent eye problems such as strain, pain, blurred vision, and watering. Predicting outcomes supports more accurate risk forecasting.\"},{\"question\":\"Which machine learning algorithms are compared in the study?\",\"answer\":\"The research evaluates and compares Naive Bayes, SVM, and KNN for predicting accuracy based on the selected dataset factors.\"},{\"question\":\"What data factors are used for prediction?\",\"answer\":\"The study uses bio factors such as age, experience, and hours of work, and then assesses the accuracy of the algorithms using a real-time dataset approach.\"}]","Eye Disease Prediction Among Corporate Employees using Machine Learning Techniques | PDF",1785731922,13,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"eye-disease-prediction-among-corporate-employees-using-machine-learning-techniques","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/healthcare/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/eye-disease-prediction-among-corporate-employees-using-machine-learning-techniques/120766/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"Why focus on eye disease prediction for corporate employees?","Question",{"text":75,"@type":76},"Employees in the IT sector spend long hours using systems, which is associated with frequent eye problems such as strain, pain, blurred vision, and watering. Predicting outcomes supports more accurate risk forecasting.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which machine learning algorithms are compared in the study?",{"text":80,"@type":76},"The research evaluates and compares Naive Bayes, SVM, and KNN for predicting accuracy based on the selected dataset factors.",{"name":82,"@type":73,"acceptedAnswer":83},"What data factors are used for prediction?",{"text":84,"@type":76},"The study uses bio factors such as age, experience, and hours of work, and then assesses the accuracy of the algorithms using a real-time dataset approach.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,109,114,117,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":115,"slug":116},40,"healthcare",{"id":118,"doc_module":4,"doc_module_name":46,"category_name":119,"show_sort_weight":120,"slug":121},8,"Research & Report",30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":21,"slug":137},19,"General","general"]