[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-122868-en":3,"doc-seo-122868-105":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},122868,4398048949847,"Eliana","https://ap-avatar.wpscdn.com/avatar/400002536579ef2da7f?_k=1778318612642679267",8,"Research & Report","A Machine Learning Model for Alzheimer’s Disease Prediction","Alzheimer’s disease (AD) is a neurodegenerative disorder that primarily impacts older adults, beginning with mild symptoms that progressively worsen over time. Although no cure exists, earlier diagnosis can lessen overall impact by enabling timely intervention. The study proposes a SMOTE-RF methodology for AD prediction using machine learning models. Experiments use the longitudinal OASIS dataset, evaluating decision tree (DT), extreme gradient boosting (XGB), and random forest (RF) on imbalanced and balanced data.","A Machine Learning Model for Alzheimer’s Disease Prediction  \nPooja Rani 1, Rohit Lamba2*, Ravi Kumar Sachdeva3, Karan Kumar4*, Celestine Iwendi5* 1MMICTBM, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, Haryana,  \nIndia  \n2,4Electronics and Communication Engineering Department, Maharishi Markandeshwar Engineering College, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala, Haryana, India-  \n133207  \n3Department of Computer Science & Engineering, Chitkara University Institute of Engineering and  \nTechnology, Chitkara University, Punjab, India  \n5School of Creative Technologies, University of Bolton, Bolton, BL3 5AB, UK [1](1poojasachdeva1886@gmail.com)[poojasachdeva1886@gmail.com](1poojasachdeva1886@gmail.com), [2](2rohitlamba14@gmail.com)[rohitlamba14@gmail.com](2rohitlamba14@gmail.com), [3](3ravisachdeva1983@gmail.com)[ravisachdeva1983@gmail.com](3ravisachdeva1983@gmail.com),  \n[4](4karan.170987@gmail.com)[karan.170987@gmail.com](4karan.170987@gmail.com), [5](5celestine.iwendi@ieee.org)[celestine.iwendi@ieee.org](5celestine.iwendi@ieee.org)  \n*Corresponding Author  \nAbstract  \nAlzheimer’s disease (AD) is a neurodegenerative disorder that mostly affects old aged people. Its symptoms are initially mild, but they get worse over time. Although this health disease has no cure, its early diagnosis can help to reduce its impacts. In this paper, a methodology SMOTE-RF is proposed for AD prediction. Alzheimer’s is predicted using machine learning (ML) algorithms. Performance of three algorithms decision tree (DT), extreme gradient boosting (XGB), and random forest (RF) are evaluated in prediction. Open Access Series of Imaging Studies (OASIS) longitudinal dataset available on Kaggle is used for experiments. Dataset is balanced using synthetic minority oversampling technique (SMOTE) . Experiments are done on both imbalanced and balanced datasets. DT obtained 73.38% accuracy, XGB obtained 83.88% accuracy and RF obtained a maximum 87.84% accuracy on the imbalanced dataset. DT obtained 83.15% accuracy, XGB obtained 91.05% accuracy and RF obtained maximum 95.03% accuracy on the balanced dataset. Maximum accuracy of 95.03% is achieved with SMOTE-RF.  \nKeywords: Extreme Gradient Boosting, Alzheimer’s Disease, Decision Tree, Random Forest.  \n1. Introduction  \nThe most prevalent neurodegenerative disorder is Alzheimer's disease. Its symptoms are firstly mild, but with time symptoms increase. Ten to twenty years before symptoms appear, the brain begins to change in the early stages of this disease. It gradually impairs thinking skills and damages memories. A group of symptoms linked to cognitive impairment make up dementia. Memory, thinking, reasoning, and the capacity to carry out daily duties are all impacted by dementia. The most typical cause of dementia is Alzheimer's disease. Over 70% of dementia patients come from low-income nations. Dementia patients face difficulty in managing their emotions. Mostly, old age persons are affected by this disease. The person suffering from this illness could have anxiety or memory problems, such as forgetting familiar names and places. The person's close friends and family have noticed that they have trouble remembering their names. A doctor can identify a patient's memory and attention issues by performing a thorough medical interview[1] .  \nAlzheimer's disease symptoms persist and worsen with time. This development impairs aperson's capacity for efficient communication, environment adaptation, and finally even the execution of simple movements. It gets harder for them to verbally express their pain or suffering. They frequently need significant support for daily tasks due to the continuing decrease in memory and cognitive abilities. At this point in the disease, Alzheimer's patients could encounter the following difficulties:  \n1. Everyday activities and personal care require round-the-clock assistance.  \n2. They lose awareness of their surroundings and recent even","cbCaisGm1T4gWeRN","https://ap.wps.com/l/cbCaisGm1T4gWeRN","pdf",523445,1,17,"English","en",105,"# Abstract\n# Introduction\n## Disease overview and impact\n## Motivation and scenario\n# Proposed methodology","[{\"question\":\"What is the main goal of this research on Alzheimer’s disease?\",\"answer\":\"To improve the accuracy and responsiveness of Alzheimer’s disease prediction by enabling earlier and more reliable diagnosis using machine learning.\"},{\"question\":\"How does the study address class imbalance in the dataset?\",\"answer\":\"It uses SMOTE to balance the dataset, and then applies the combined SMOTE-RF approach for prediction experiments.\"},{\"question\":\"Which machine learning algorithms are evaluated, and how is performance measured?\",\"answer\":\"Decision tree (DT), extreme gradient boosting (XGB), and random forest (RF) are evaluated using predictive performance shown as accuracy on both imbalanced and balanced datasets.\"}]","A Machine Learning Model for Alzheimer’s Disease Prediction | PDF",1785813429,43,{"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},"a-machine-learning-model-for-alzheimers-disease-prediction","",{"@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/a-machine-learning-model-for-alzheimers-disease-prediction/122868/",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","2026-08-04",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 is the main goal of this research on Alzheimer’s disease?","Question",{"text":75,"@type":76},"To improve the accuracy and responsiveness of Alzheimer’s disease prediction by enabling earlier and more reliable diagnosis using machine learning.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the study address class imbalance in the dataset?",{"text":80,"@type":76},"It uses SMOTE to balance the dataset, and then applies the combined SMOTE-RF approach for prediction experiments.",{"name":82,"@type":73,"acceptedAnswer":83},"Which machine learning algorithms are evaluated, and how is performance measured?",{"text":84,"@type":76},"Decision tree (DT), extreme gradient boosting (XGB), and random forest (RF) are evaluated using predictive performance shown as accuracy on both imbalanced and balanced datasets.","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"]