[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125877-en":3,"doc-seo-125877-105":31,"detail-sidebar-cat-0-en-105":93},{"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":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},125877,1099523885336,"Violet","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",7,"Healthcare","Brain Stroke Prediction Model - Based SMOTE and Machine Learning Algorithms","A brain stroke is a critical medical emergency that can lead to disability and death, making early pre-diagnosis essential to reduce complications. This study performs an analytical pipeline on a brain stroke dataset using the KNIME platform, applying machine learning components including random forest, decision tree learner, gradient boosted trees learner, and logistic regression. Data preprocessing addresses class imbalance with SMOTE, while feature selection uses forward feature selection, backward elimination, and genetic algorithms. Results show logistic regression achieves the best performance after forward and backward feature selection.","Brain Stroke Prediciton Model Based SMOTE and Machine Learning  \nAlgorithms  \n1Alhussain Waad Mohammed, 1Hwraa Kareem Hmoud, 1Ahmed Mohmed Abd Alzahra, 1Ahmad Muneathir  \nSukar and 2*Alaa Khalaf Hamoud  \n1Department of Computer Information Systems,  \n2Department of Cybersecurity,  \nCollege of Computer Science and Information Technology,  \nUniversity of Basrah,  \nBasrah, Iraq.  \n*Corresponding Author: [alaa.hamoud@uobasrah.edu.iq](alaa.hamoud@uobasrah.edu.iq)  \n\n| Article Info Article history:\u003Cbr>Article received on 10 01 2024\u003Cbr>Received in revised form 10 02 2024\u003Cbr>Keywords:\u003Cbr>Brain Stroke; Feature Selection; SMOTE, Decision Tree; Logistic Regression; Random Forest; Gradient Boosted Trees; KNIME. | ABSTRACT: A brain stroke is a critical medical emergency that causes disability and death. The pre-diagnosis of this case can reduce the complications and problems that affect the brain as a result of being affected by the complications that occur during the injury. This study listsan analysis process on a brain stroke dataset using the KNIME tool, which provides a set of different machine learning components such as random forest, Decision Tree Learner, Gradient Boosted Trees Learner, and Logistic Regression algorithms. The problem of imbalanced data will be handled as part of data preprocessing. The factors that affect the brain stroke will be explored based on feature selection approaches such as forward feature selection, backward feature elimination, genetic algorithms, and random. The aim is to build a model that helps doctors diagnose the disease accurately based on the results we obtained from the study and analysis. The results showed that logistic regression outperformed the other algorithms after applying the algorithm with forward feature selection and backward feature elimination. |\n| --- | --- |\n\n1. INTRODUCTION  \nAccording to the World Stroke Organization, 13 million people get a stroke each year, and approximately 5.5 million people will die as a result. So stroke is one of disorder leading causes of death and disability worldwide, and that is why its imprint is serious in all aspects of life [1]–[4] . Stroke not only affects the patient but also affects the patient’s social environment, family, and workplace. In addition, contrary to popular belief, it can happen to anyone at any age, regardless of gender or physical condition. The functioning of various human body parts is essential to our existence. Strokes, a serious health condition, are a major cause of mortality, especially prevalent in individuals over 65 years [5], [6] . Similar to heart attacks impacting the heart, strokes impair  \nbrain function. They are caused either by a disruption in the brain’s blood supply or by bleeding from ruptured brain vessels. This blockage or rupture prevents blood and oxygen from nourishing brain tissue. Strokes rank as the fifth leading cause of death globally in both developed and developing countries. Immediate medical attention significantly increases a stroke victim’s recovery prospects. Delay in treatment can lead to death, irreversible damage, or severe brain impairment. Various factors contribute to stroke risk, including diet, sedentary lifestyle, alcohol consumption, tobacco use, personal and medical history, and other complications as outlined by the National Heart, Lung, and Blood Institutes. Recent advancements in clinical and medical services have been propelled by artificial intelligence, machine learning, and data science. Machine learning, a cornerstone of the current era, is employed for the  \nearly prediction of numerous health issues, including strokes. Early detection is vital for effective stroke treatment. In healthcare, machine learning plays an essential role in diagnosing and predicting diseases. Stroke prediction currently utilizes machine-learning algorithms. Managing large medical data sets requires robust data analysis tools, and AI’s role in medicine is a key research area. AI systems can ide","cbCaioBKR679vlrf","https://ap.wps.com/l/cbCaioBKR679vlrf","pdf",330450,6,1,9,"English","en",105,"# Abstract\n# Introduction\n## Stroke background and risk factors\n## Role of machine learning in stroke prediction\n## Class imbalance and SMOTE\n# Study aim and methodology\n## Algorithms and evaluation plan","[{\"question\":\"Why is early brain stroke prediction important?\",\"answer\":\"Early prediction supports timely medical intervention, which improves recovery prospects and reduces the risk of irreversible brain damage caused by delayed treatment.\"},{\"question\":\"How does the study handle imbalanced data?\",\"answer\":\"The study applies SMOTE during data preprocessing to adjust the distribution of classes by synthesizing minority examples.\"},{\"question\":\"Which algorithm performed best in the study results?\",\"answer\":\"Logistic regression outperformed the other evaluated algorithms after applying forward feature selection and backward feature elimination.\"}]","Brain Stroke Prediction Model - Based SMOTE and Machine Learning Algorithms | PDF",1785901788,23,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":88,"head_meta":90,"extra_data":92,"updated_unix":29},"brain-stroke-prediction-model-based-smote-and-machine-learning-algorithms","",{"@graph":37,"@context":87},[38,55,70],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,52],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/document/","Document",2,{"item":50,"name":12,"@type":44,"position":51},"https://docshare.wps.com/document/healthcare/",3,{"item":53,"name":13,"@type":44,"position":54},"https://docshare.wps.com/document/brain-stroke-prediction-model-based-smote-and-machine-learning-algorithms/125877/",4,{"url":53,"name":13,"@type":56,"author":57,"headline":13,"publisher":59,"fileFormat":62,"inLanguage":24,"description":14,"dateModified":63,"datePublished":64,"encodingFormat":62,"isAccessibleForFree":65,"interactionStatistic":66},"DigitalDocument",{"name":9,"@type":58},"Person",{"url":42,"name":60,"@type":61},"DocShare","Organization","application/pdf","2026-08-24","2026-08-05",true,{"@type":67,"interactionType":68,"userInteractionCount":20},"InteractionCounter",{"@type":69},"ViewAction",{"@type":71,"mainEntity":72},"FAQPage",[73,79,83],{"name":74,"@type":75,"acceptedAnswer":76},"Why is early brain stroke prediction important?","Question",{"text":77,"@type":78},"Early prediction supports timely medical intervention, which improves recovery prospects and reduces the risk of irreversible brain damage caused by delayed treatment.","Answer",{"name":80,"@type":75,"acceptedAnswer":81},"How does the study handle imbalanced data?",{"text":82,"@type":78},"The study applies SMOTE during data preprocessing to adjust the distribution of classes by synthesizing minority examples.",{"name":84,"@type":75,"acceptedAnswer":85},"Which algorithm performed best in the study results?",{"text":86,"@type":78},"Logistic regression outperformed the other evaluated algorithms after applying forward feature selection and backward feature elimination.","https://schema.org",{"og:url":53,"og:type":89,"og:title":13,"og:site_name":60,"og:description":14},"article",{"robots":91,"canonical":53},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":94},[95,99,103,107,112,116,119,124,128,131,135],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":96,"show_sort_weight":97,"slug":98},"Story & Novel",90,"story-novel",{"id":48,"doc_module":4,"doc_module_name":47,"category_name":100,"show_sort_weight":101,"slug":102},"Literature",80,"literature",{"id":54,"doc_module":4,"doc_module_name":47,"category_name":104,"show_sort_weight":105,"slug":106},"Exam",70,"exam",{"id":108,"doc_module":4,"doc_module_name":47,"category_name":109,"show_sort_weight":110,"slug":111},5,"Comic",60,"comic",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},"Technology",50,"technology",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":117,"slug":118},40,"healthcare",{"id":120,"doc_module":4,"doc_module_name":47,"category_name":121,"show_sort_weight":122,"slug":123},8,"Research & Report",30,"research-report",{"id":22,"doc_module":4,"doc_module_name":47,"category_name":125,"show_sort_weight":126,"slug":127},"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":47,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":47,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":47,"category_name":137,"show_sort_weight":108,"slug":138},19,"General","general"]