[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117059-en":3,"doc-seo-117059-105":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},117059,3848291630094,"Emma Wilson","https://eur-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45",7,"Healthcare","Disease Prediction using Machine Learning - Abstract - Introduction - Literature Review","A disease prediction system based on predictive modelling determines a user’s likely illness from input signs and provided symptoms. The system evaluates symptom data and outputs the probability of an illness occurring. A decision tree classifier is used to calculate disease likelihood, and machine learning methods are highlighted for improving prediction precision. The approach is motivated by the need to help end users anticipate chronic or irreversible conditions without consulting a doctor, while examining both structured and unstructured materials.","Disease Prediction using Machine Learning  \nMohd. Nadeem Khan 1 and Ankita Srivastava2  \n1Student, Department of Computer Science and Engineering, Integral University Lucknow, INDIA 2Professor, Department of Computer Science and Engineering, Integral University Lucknow, INDIA  \n[1](1Corresponding Author: nadeemk0076@gmail.com)[Corresponding Author: nadeemk0076@gmail.com](1Corresponding Author: nadeemk0076@gmail.com)  \nReceived: 30-05-2023 Revised: 17-06-2023 Accepted: 30-06-2023  \nABSTRACT  \nBased on predictive modelling, a disease prediction system determines the user's illness from the signs they provide as input to the system. The system evaluates the user's symptoms as input and outputs the likelihood that the illness will occur. Utilizing a decision tree classifier, disease prediction is accomplished. The likelihood of the illness is calculated by a decision tree classifier. More and more organisations in the biological and healthcare sectors are turning to big data to aid in early disease discovery and better serve their patients. The development of a system that will allow people to forecast chronic illnesses without having to see a doctor or medical professional for a diagnostic is necessary by watching patient signs and using a variety of machine learning modelling methods, different illnesses can be identified. Text and organised data processing do not follow any standard method. The suggested paradigm would examine both organised and random material. Prediction precision can be increased through machine learning. There is a need to research and develop a system that will allow an enduser to anticipate irreversible illnesses without having to consult a specialist or doctor for a diagnostic. To identify different diseases by analysing patient symptoms using various techniques of Machine Learning Algorithms. Thereis no proper technique for managing text and structured data. Both organised and unstructured material will be examined by the Suggested algorithm. Artificial Learning will improve prediction accuracy.  \nKeywords-- Disease Prediction, Machine Learning, Decision Tree Classifier, Healthcare, Chronic Illnesses, Predictive Model  \nI. INTRODUCTION  \nProgramming machines to perform better using sample data or historical data is known as machine learning. Machine learning is the study of computer programs that gain knowledge from past experience and data. The training and testing stages of a machine learning system. disease diagnosis based on the signs and medical background of the patient Machine learning technology has improved over the years.  \nThe medical field now has an incomparable platform thanks to machine learning technology, making it possible to fix healthcare problems quickly. Machine learning is being used to keep full hospital data. With the  \naid of machine learning technology, physicians can more accurately identify and treat patients, which improves patient healthcare services. Machine learning technology enables creating models to analyze data rapidly and deliver findings quicker.  \nThe use of machine learning in the medical sector is best illustrated by the case of healthcare. To improve the accuracy from large amounts of data, work is currently being done on unstructured and written data. The current will use linear, KNN, and decision tree algorithms for illness prognosis. The collection of references at the conclusion of the paper should be cited in the same sequence as the main text.  \nII. LITERATURE REVIEW  \nThere have been many research conducted on the topic of disease prediction utilizing various machine learning approaches and algorithms that medical institutions can apply. In this paper, some of those investigations are reviewed along with the methods and findings they employed.  \nIn their study, MIN CHEN et al. [1] suggested a disease prediction system based on machine learning techniques. He employed approaches such as CNNUDRP, CNN-MDRP, Naive Bayes, K-Nearest Neighbor, and Decision Tre","cbCaikXtOW83zSex","https://ap.wps.com/l/cbCaikXtOW83zSex","pdf",294057,1,5,"English","en",105,"# Abstract\n# Introduction\n# Literature Review","[{\"question\":\"How does the proposed disease prediction system work?\",\"answer\":\"It takes user-provided signs and symptoms as input, evaluates them, and outputs the likelihood that a disease will occur.\"},{\"question\":\"Which machine learning model is mentioned for calculating disease likelihood?\",\"answer\":\"A decision tree classifier is used to accomplish disease prediction and compute the illness likelihood.\"},{\"question\":\"Why does the paper emphasize using machine learning for chronic illness prediction?\",\"answer\":\"It aims to enable end users to anticipate irreversible or chronic illnesses without requiring consultation with a doctor, improving early discovery and prediction accuracy.\"}]","Disease Prediction using Machine Learning - Abstract - Introduction - Literature Review | PDF",1785673489,13,{"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},"disease-prediction-using-machine-learning-abstract-introduction-literature-review","",{"@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/disease-prediction-using-machine-learning-abstract-introduction-literature-review/117059/",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","2026-08-02",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},"How does the proposed disease prediction system work?","Question",{"text":75,"@type":76},"It takes user-provided signs and symptoms as input, evaluates them, and outputs the likelihood that a disease will occur.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which machine learning model is mentioned for calculating disease likelihood?",{"text":80,"@type":76},"A decision tree classifier is used to accomplish disease prediction and compute the illness likelihood.",{"name":82,"@type":73,"acceptedAnswer":83},"Why does the paper emphasize using machine learning for chronic illness prediction?",{"text":84,"@type":76},"It aims to enable end users to anticipate irreversible or chronic illnesses without requiring consultation with a doctor, improving early discovery and prediction accuracy.","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"]