[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118177-en":3,"doc-seo-118177-105":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},118177,8796095461564,"Liam","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Multiple Disease Prediction System - Machine Learning - Early Diagnosis and Risk Forecasting","Machine learning advancements drive healthcare transformation by enabling predictive models for early disease diagnosis. This report presents the Multiple Disease Prediction System (MDPS), forecasting the likelihood of multiple diseases from patient data such as medical history, lifestyle, and demographics. It targets early detection to reduce healthcare challenges and supports proactive risk assessment and tailored guidance. Core steps include data preparation, feature selection, and model training with disease detection. Ethical and effective deployment requires attention to data privacy, interpretability, and ongoing improvements.","Multiple Disease Prediction System using Machine Learning  \nAhad Rehman 1, Shikha Singh2, Vineet Singh3, Bramah Hazela4  \n1,2,3,4 Department of Computer Science and Engineering, Amity School of Engineering and Technology, Lucknow, Amity University, Uttar Pradesh, India [1](1ahad.rehman@s.amity.edu)[ahad.rehman@s.amity.edu](1ahad.rehman@s.amity.edu), [2](2ssingh8@lko.amity.edu)[ssingh8@lko.amity.edu](2ssingh8@lko.amity.edu), [3](3vsingh@lko.amity.edu)[vsingh@lko.amity.edu](3vsingh@lko.amity.edu), [4](4bhazela@lko.amity.edu)[bhazela@lko.amity.edu](4bhazela@lko.amity.edu)  \n\n| How to cite this paper: A. Rehman, S. Singh, V. Singh, B. Hazela, “Multiple Disease Prediction System using Machine Learning,” Journal of Informatics Electrical and Electronics Engineering (JIEEE), 2024.\u003Cbr>[https://doi.org/10.54060/a2zjournal](https://doi.org/10.54060/a2zjournal) |\n| --- |\n| s.jieee.110\u003Cbr>Received: 05/01/2024\u003Cbr>Accepted: 30/04/2024\u003Cbr>Online First: 27/05/2024\u003Cbr>Copyright © 2024 The Author(s) .\u003Cbr>This work is licensed under the Creative Commons Attribution International License (CC BY 4.0) . [http://creativecommons.org/license](http://creativecommons.org/license) |\n| s/by/4 .0/\u003Cbr>  Open Access  |\n\nAbstract  \nMachine learning advancements have spurred a revolution in healthcare by making it possible to create prediction models for early disease diagnosis. This report introduces the Multiple Disease Prediction System (MDPS), a state-of-the-art approach that uses machine learning to forecast the likelihood of several diseases based on patient data, including medical history, lifestyle, and demographics. The MDPS addresses the growing difficulties in healthcare by focusing on the early detection of multiple diseases. Some of its crucial components include data preparation, feature selection, model training and disease Detection. Despite advantages like early detection and cost savings, dealing with data privacy, model interpretability, and continuous improvements is essential for MDPS's ethical and efficient usage in healthcare. As a result, MDPS has a significant potential to enhance public health and minimize the difficulties associated with chronic illnesses.  \nKeywords  \nMultiple Disease, machine learning, random forest classifier, KNN, logistic regression, liver disease, kidney disease, heart disease, diabetes.  \n1. Introduction  \nThe integration of machine learning (ML) techniques into healthcare has revolutionized disease prediction and treatment, with ML algorithms driving the creation of numerous disease prediction systems. These systems utilize data-driven methodologies to assess targeted multiple medical factors simultaneously, enabling proactive healthcare through early identification, personalized risk assessment, and therapies. This introduction highlights the transformative potential of ML-based multiple illness prediction systems in improving patient outcomes and advancing medical practices.  \n1.1 Objective  \nThe objective of this report is to develop and implement a smart multi disease prediction system leveraging machine learning algorithms. The focus is on creating a robust system that utilizes patients’ data and predicts to provide an accurate disease prediction. By harnessing advanced technology, the aim is to empower medical field with precise prediction and detection of diseases guidance using multiple entries from the user, optimizing accuracy and enhancing overall system scalability and sustainability.  \n1.2. Motivation  \nThe motivation behind choosing the Multiple Disease Prediction System (MDPS) stems from the urgent need to tackle healthcare challenges, especially in early disease detection and prevention. Integrating machine learning into disease prediction aims to empower individuals and healthcare providers with precise insights for early disease identification. By harnessing advanced machine learning techniques, MDPS offers personalized disease predictions based on diverse datasets, fostering proactive healt","cbCaiijJ2IT0OQxm","https://ap.wps.com/l/cbCaiijJ2IT0OQxm","pdf",473311,1,13,"English","en",105,"# Abstract\n# Keywords\n# 1. Introduction\n## 1.1 Objective\n## 1.2 Motivation\n## 1.3 Problem Statement\n## 1.4 About Multiple Disease Prediction System","[{\"question\":\"What problem does the Multiple Disease Prediction System (MDPS) address?\",\"answer\":\"MDPS targets the challenge that current healthcare often relies on disease-specific models, which creates fragmentation and inefficiencies. It provides integrated multi-disease predictions to improve diagnosis accuracy and operational efficiency.\"},{\"question\":\"What patient data does MDPS use for disease likelihood forecasting?\",\"answer\":\"MDPS uses patient information including medical history, lifestyle, and demographics to estimate the likelihood of several diseases.\"},{\"question\":\"Which stages are mentioned for building the MDPS models?\",\"answer\":\"The report highlights data preparation, feature selection, model training, and disease detection as key components.\"}]","Multiple Disease Prediction System - Machine Learning - Early Diagnosis and Risk Forecasting | PDF",1785682008,33,{"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},"multiple-disease-prediction-system-machine-learning-early-diagnosis-and-risk-forecasting","",{"@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/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/multiple-disease-prediction-system-machine-learning-early-diagnosis-and-risk-forecasting/118177/",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},"What problem does the Multiple Disease Prediction System (MDPS) address?","Question",{"text":75,"@type":76},"MDPS targets the challenge that current healthcare often relies on disease-specific models, which creates fragmentation and inefficiencies. 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