[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-116997-en":3,"doc-seo-116997-105":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},116997,8796095360427,"Lucas Martin","https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d",8,"Research & Report","HYPOTHYROID DISEASE ANALYSIS - USING MACHINE LEARNING","Hypothyroidism is a common thyroid illness, often affecting predominantly female patients, and many people remain unaware of it until it becomes more serious. Early detection and accurate diagnosis are critical for effective medical treatment and prevention of disease progression. This project applies machine learning to hypothyroidism prediction using thyroid function-related measures from a UCI dataset. Logistic Regression, Decision Trees, and Naive Bayes are trained and evaluated with hyperparameter tuning to assess model performance.","California State University, San Bernardino  \nCSUSB ScholarWorks  \n\n| Electronic Theses, Projects, and Dissertations | Office of Graduate Studies |\n| --- | --- |\n| 12-2023\u003Cbr>HYPOTHYROID DISEASE ANALYSIS BY USING MACHINE LEARNING\u003Cbr>SANJANA SEELAM\u003Cbr>Follow this and additional works at: [https://scholarworks.lib.csusb.edu/etd](https://scholarworks.lib.csusb.edu/etd)\u003Cbr> Part of the Other Computer Engineering Commons, Other Computer Sciences Commons, Programming Languages and Compilers Commons, and the Theory and Algorithms Commons |  |\n\nRecommended Citation  \nSEELAM, SANJANA, \"HYPOTHYROID DISEASE ANALYSIS BY USING MACHINE LEARNING\" (2023) . Electronic Theses, Projects, and Dissertations. 1814.  \n[https://scholarworks.lib.csusb.edu/etd/1814](https://scholarworks.lib.csusb.edu/etd/1814)  \nThis Project is brought to you for free and open access by the Office of Graduate Studies at CSUSB ScholarWorks. It has been accepted for inclusion in Electronic Theses, Projects, and Dissertations by an authorized administrator of CSUSB ScholarWorks. For more information, please contact [scholarworks@csusb.edu](scholarworks@csusb.edu).  \nHYPOTHYROID DISEASE ANALYSIS BY USING MACHINE LEARNING  \nA Project Presented to the Faculty of  \nCalifornia State University, San Bernardino  \nIn Partial Fulfillment of the Requirements for the Degree Master of Science in  \nComputer Science  \nby Sanjana Seelam December 2023  \nHYPOTHYROID DISEASE ANALYSIS BY USING MACHINE LEARNING  \nA Project Presented to the Faculty of  \nCalifornia State University, San Bernardino  \nby  \nSanjana Seelam  \nDecember 2023  \nApproved by:  \nDr. Qingquan Sun, Advisor, Computer Science and Engineering Dr. Jennifer Jin, Committee Member  \nDr. Yan Zhang, Committee Member  \n© Sanjana Seelam  \nABSTRACT  \nThyroid illness frequently manifests as Hypothyroidism. It is evident that people with hypothyroidism are primarily female. Because the majority of people are unaware of the illness, it is quickly becoming more serious. It is crucial to catch it early on so that medical professionals can treat it more effectively and prevent it from getting worse. Machine Learning illness prediction is a challenging task. Disease prediction is aided greatly by machine learning. Once more, unique feature selection strategies have made the process of disease assumption and prediction easier.  \nTo properly monitor and cure this illness, accurate detection is essential. In order to build models that can forecast the development of hypothyroidism. In this project, we utilized machine learning approaches such Logistic Regression, Decision Trees, and Naive Bayes. Here, we used thyroid function-related measures and characteristics from a UCI Machine learning repository dataset.  \nThe main goals were to properly assess each machine learning model's performance and fine-tune its hyperparameters. With an accuracy rate of 99.87%, the findings of this study generated the model's ability to predict hypothyroidism were pretty remarkable.  \nThis high degree of accuracy shows how useful these machine learning algorithms are as diagnostic and therapeutic tools for hypothyroid patients early on. This experiment demonstrates the potential of machine learning in healthcare and has an impact on diagnosis.  \niii  \nACKNOWLEDGEMENTS  \nAs a chair of the committee Dr. Qingquan Sun, I would like to take this opportunity to thank all of you for your unwavering support and dedication to my academic career. I would also like to sincerely thank Jennifer Jin and Dr. Yang Zhang, who is on my committee.Your belief in my ability to serve on my committee has helped me along the way in my endeavour. I am grateful for your belief in my ability to perform this project.  \nIn addition, I would like to thank all my university professors, who shaped my academic progress. Your advice, knowledge and support have been very important to my academic success. I am indeed California State University, San Bernardino School of Computer Science providing suc","cbCaicCBQECeC8Lk","https://ap.wps.com/l/cbCaicCBQECeC8Lk","pdf",1137723,1,48,"English","en",105,"# ABSTRACT\n# ACKNOWLEDGEMENTS\n# LIST OF FIGURES\n# CHAPTER ONE: INTRODUCTION\n## Background\n## Motivation\n## Overview of Dataset and Problem Statement\n# CHAPTER TWO: LITERATURE REVIEW\n# CHAPTER THREE: SYSTEM MODEL\n## Data Preprocessing\n## Data Collection\n## Data Type and Size\n## Data Cleaning\n## Feature Selection\n# CHAPTER FOUR: MACHINE LEARNING","[{\"question\":\"Why is early detection of hypothyroidism important?\",\"answer\":\"Early detection enables more effective treatment by medical professionals and helps prevent the illness from worsening.\"},{\"question\":\"Which machine learning models were used for hypothyroidism prediction?\",\"answer\":\"The project used Logistic Regression, Decision Trees, and Naive Bayes.\"},{\"question\":\"What data source and features were used to build the models?\",\"answer\":\"Models used thyroid function-related measures and characteristics from a UCI machine learning repository dataset.\"}]","HYPOTHYROID DISEASE ANALYSIS - USING MACHINE LEARNING | PDF",1785673016,121,{"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},"hypothyroid-disease-analysis-using-machine-learning","",{"@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/hypothyroid-disease-analysis-using-machine-learning/116997/",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},"Why is early detection of hypothyroidism important?","Question",{"text":75,"@type":76},"Early detection enables more effective treatment by medical professionals and helps prevent the illness from worsening.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which machine learning models were used for hypothyroidism prediction?",{"text":80,"@type":76},"The project used Logistic Regression, Decision Trees, and Naive Bayes.",{"name":82,"@type":73,"acceptedAnswer":83},"What data source and features were used to build the models?",{"text":84,"@type":76},"Models used thyroid function-related measures and characteristics from a UCI machine learning repository dataset.","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},[93,97,101,105,110,115,120,123,128,131,135],{"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":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]