[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124922-en":3,"doc-seo-124922-105":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},124922,4398048950312,"Violet","https://ap-avatar.wpscdn.com/avatar/400002538284de19e3c?_k=1778320343897328908",8,"Research & Report","Implementation of Child Healthcare System by Using Machine Learning Techniques","The article presents a paediatric healthcare approach for children under five, aiming to track development from infancy to age five and to support treatment outside hospitals. Parents can upload children’s information through a digital system to monitor growth status, detect unhealthy behaviours, and anticipate potential chronic diseases. The system also reports nearby health factors such as vaccination coverage, then provides tailored solutions to reduce health risks quickly. Machine learning methods are used to forecast child healthcare via a decision tree for CHS, MySQL reminders for immunizations, and the K-means Elbow technique for maternal registration and notification.","Journal of Advanced Zoology  \nISSN: 0253-7214  \nVolume 44 IssueS-5 Year 2023 Page 723:732  \nImplementation of Child Healthcare System by Using Machine Learning  \nTechniques  \nMahesh Ashok Mahant1, P. Vidyullatha2  \n1Research Scholar, Department of Computer Science and Engineering, Koneru Lakshmaiah Education  \nFoundation, Vaddeswaram, AP, India  \n2Associate Professor, Department of Computer Science and Engineering, Koneru Lakshmaiah Education  \nFoundation, Vaddeswaram, AP, India  \n[Corresponding Author E-mail:](Corresponding Author E-mail:1maheshamahant@gmail.com)[1](Corresponding Author E-mail:1maheshamahant@gmail.com)[maheshamahant@gmail.com](Corresponding Author E-mail:1maheshamahant@gmail.com), [2](2pvidyullatha@kluniversity.in)[pvidyullatha@kluniversity.in](2pvidyullatha@kluniversity.in)  \n\n| Article History\u003Cbr>Received: 06 June 2023\u003Cbr>Revised: 09 September 2023\u003Cbr>Accepted:14 September 2023\u003Cbr>CC License\u003Cbr>CC-BY-NC-SA 4.0 | Abstract\u003Cbr>The focus of the article waspaediatric healthcare for children under the age of five. This approach was designed with the goal of tracking children's development from infancy to age five. The goal of the child healthcare system is to provide treatment for growing children outside of hospitals. Nowadays, because we live in a purely digital age, we can provide parents the ability to monitor their child's development while they remain in their own country. Children's info can be uploaded by their parents. The system can then assess the present development and growth status, spot unhealthy behaviours, anticipate potential chronic diseases, report health-related factors (such as vaccination coverage) that's in the immediate surroundings, and finally offer tailored solutions to avert health hazards as quickly as possible. The studies included in this study concentrate on utilising machine learning algorithms to forecast child healthcare. We put the system into practise using a decision tree for CHS, MySQL for reminders about immunizations, and the K-means Elbow technique for maternal registration and notification.\u003Cbr>Keywords: Child Healthcare System, Decision Tree, Disease Health Risk. |\n| --- | --- |\n\n1. INTRODUCTION  \nThe issues with the current healthcare systems are put out in this effort. Motivated by both the poor hospital interventions and the high under-five death rate. In order to assist the current health system, we suggested using computer technology to provide missing health services, such as kid risk query and results. The suggested system will solve the stated issues and accomplish the project's objective.  \nDiseases are more likely to affect kids below the age of five. According to the WHO, a total of 6.3 million babies died annually, and over half of those deaths are preventable or treatable with access to low-cost, straightforward therapies. These children's parents typically have a large family but little sparetime, energy, money, or risk tolerance [1] . Despite the fact that the majority of families are responsible, they struggle to get their kids to the doctor on a regular basis. Due to a lack of available professional knowledge, local health communities might not be able to provide effective therapy. While the capital hospital often requests that parents await for a consultation due to comparatively insufficient medical resources in comparison to a high patient volume [2] . They cannot anticipate receiving sufficient justification during the medical checkup or a prompt study of the child's behaviours when they see the doctor. Because the specialists do not have adequate information about the child's medical history, they are only able to offer advice on present diseases rather than latent disorders [3] . Along with internal health risks and lifestyle choices, the outside environment also contributes to a child's risk factors in  \n-723- Available online at: [https://jazindia.com](https://jazindia.com)  \nImplementation of Child Healthcare System by Using Machine Learning Te","cbCaibUOOt2yduCK","https://ap.wps.com/l/cbCaibUOOt2yduCK","pdf",376989,1,10,"English","en",105,"# Abstract\n# Introduction","[{\"question\":\"What problem does the child healthcare system address?\",\"answer\":\"It targets shortcomings in existing healthcare services and helps reduce under-five healthcare gaps by enabling risk assessment and guidance beyond hospital visits.\"},{\"question\":\"How does the proposed system help parents monitor their children?\",\"answer\":\"Parents upload children’s data, after which the system assesses development and growth status, identifies unhealthy behaviours, and flags potential chronic disease risks.\"},{\"question\":\"Which machine learning and implementation components are mentioned?\",\"answer\":\"The study uses a decision tree for CHS, MySQL to manage immunization reminders, and the K-means Elbow technique to support maternal registration and notification.\"}]","Implementation of Child Healthcare System by Using Machine Learning Techniques | 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