[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-117358-en":3,"doc-seo-117358-105":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},117358,687197207639,"Asher","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","Heart Disease Prediction Using Machine Learning Alghorithms - Master’s thesis","The qualification work researches and develops machine learning methods for predicting heart disease and identifying behavioral risk factors that influence cardiovascular disease (CVD) prevention. Using health-related information, the study trains models to estimate the likelihood of heart problems and determine the presence of the issue based on analyzed data. The results are intended to support doctors in establishing more accurate diagnoses and improving risk assessment and prevention decisions through data-driven predictions.","Faculty of Computer Information System and Software Engineering  \n(full name of faculty)  \nDepartment of Computer Science  \n(full name of department)  \nQUALIFYING PAPER  \nFor the degree of  \nMaster’s thesis  \n\n| topic: | (degree name)\u003Cbr>Heart Disease Prediction Using Machine Learning Alghorithms |\n| --- | --- |\n|  |  |\n\nSubmitted by: student  IV  course, group  ICAm-62   \nspecialty  124 System analysis   \n(шифр і назва спеціальності)  \nAli Zulaikha Naadu  \n(signature) (surname and initials)  \nSupervisor    Zolotyi R.Z.   \n(signature) (surname and initials)  \nStandards verified by      \n(signature) (surname and initials)  \nHead of Department    Bodnarchuk I.O.   \n(signature) (surname and initials)  \nReviewer      \n(signature) (surname and initials)  \nTernopil  \nFaculty Faculty of Computer Information System and Software Engineering   \n(full name of faculty)  \nDepartment Department of Computer Science   \n(full name of department)  \nAPPROVED BY  \nHead of Department  \nBodnarchuk I.O.  \n6. Advisors of paper chapters  \n\n| Chapter | Advisor’s surname, initials and position | Signature, date |  |\n| --- | --- | --- | --- |\n|  |  | assignment was\u003Cbr>given by | assignment\u003Cbr>was received by |\n| Occupational health and |  |  |  |\n| emergency safety |  |  |  |\n|  |  |  |  |\n|  |  |  |  |\n|  |  |  |  |\n|  |  |  |  |\n|  |  |  |  |\n\n7. Date of receiving the assignment  20.01.2025   \nTIME SCHEDULE  \n\n| LN | Paper stages | Paper stages deadlines | Notes |\n| --- | --- | --- | --- |\n| 1 | Analysis of the task for qualifying work. Selection |  | Completed |\n|  | and work with literary sources. |  |  |\n| 2 | Writing chapter 1 |  | Completed |\n| 3 | Writing chapter 2 |  | Completed |\n| 4 | Writing chapter 3 |  | Completed |\n| 5 | Writing chapter 4 |  | Completed |\n| 6 | Standartization control |  | Completed |\n| 7 | Plagiarism check |  | Completed |\n| 8 | Preliminary defense of qualifying paper |  | Completed |\n| 9 | Defense of qualifying paper |  |  |\n|  |  |  |  |\n|  |  |  |  |\n|  |  |  |  |\n|  |  |  |  |\n|  |  |  |  |\n|  |  |  |  |\n|  |  |  |  |\n|  |  |  |  |\n|  |  |  |  |\n|  |  |  |  |\n|  |  |  |  |\n|  |  |  |  |\n|  |  |  |  |\n\nStudent    Ali Zulaikha Naadu   \n(signature) (surname and initials)  \nPaper supervisor    Zolotyi R.Z.   \n(signature) (surname and initials)  \nANNOTATION  \nHeart Disease Prediction Using Machine Learning Alghorithms // Diploma thesis Master’s degree // Ali Zulaikha Naadu // Ternopil’ Ivan Puluj National Technical University, Faculty of Computer Information System and Software Engineering, Department of Computer Science // Ternopil', 2025 // P.   , Fig.–   , Tables –   , Annexes –   , References –   .  \nKеуwоrds: machine learning, ssz, pytorch, program, code.  \nThe purpose of the qualification work is to research and develop machine learning methods that can be effectively applied to predict heart disease and correct behavioral risk factors in the prevention of cardiovascular disease (CVD) .  \nDuring the qualification work, the task was to predict the likelihood of heart problems in people based on information about their health and accurately identify the problem, thanks to machine learning algorithms. The results of this study can be used by doctors to establish an accurate diagnosis of patients' hearts based on the analyzed data, which will predict the possibility of developing heart disease.  \nCONTENT  \nINTRODUCTION..................................................................................................... 6  \n1. ANALYSIS OF DEVELOPMENTS ON THE TOPIC OF THE WORK............ 8  \n1.1. Justification of the relevance of the chosen topic .................................... 8  \n1.2. Areas of application ............................................................................... 10  \n1.3. Justification of the feasibility of improving existing solutions ............. 12  \n1.4. Problem statement .................................................................................. 13  \n2. PRINCIPLES OF MACHINE LEARNI","cbCaiavlHD2WY1AP","https://ap.wps.com/l/cbCaiavlHD2WY1AP","pdf",2860189,1,76,"English","en",105,"# Introduction\n## Analysis of developments on the topic of the work\n## Principles of machine learning and data processing algorithms\n## Development of program structure and algorithms\n## Safety of life and basic labor protection\n# Conclusions\n# References","[{\"question\":\"What is the purpose of the qualification work?\",\"answer\":\"To research and develop machine learning methods that predict heart disease and help correct behavioral risk factors for CVD prevention.\"},{\"question\":\"How does the study approach heart disease prediction?\",\"answer\":\"It predicts the likelihood of heart problems using information about individuals’ health and applies machine learning algorithms to identify the problem.\"},{\"question\":\"How can the results be used in practice?\",\"answer\":\"Doctors can use the study outcomes to support more accurate heart diagnosis based on the analyzed data and to predict the possibility of developing heart disease.\"}]","Heart Disease Prediction Using Machine Learning Alghorithms - 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