[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126588-en":3,"doc-seo-126588-105":30,"detail-sidebar-cat-0-en-105":92},{"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":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},126588,687207017582,"Himbo","https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d",7,"Healthcare","A Survey on an Effective Identification and Analysis for Brain Tumour Diagnosis using Machine Learning Technique","Image analysis remains a central medical challenge because it supports severity assessment and outcome forecasting. However, noise-trimming performance declines when training uses more complex images, which can lower prediction accuracy. A novel machine learning prediction framework is proposed to predict brain tumours and evaluate severity using MRI brain scans. Boosting-based training produces strong error-pruning results, and feature analysis plus tumour prediction are completed using the proposed solution. Evaluation in Python includes comparative analysis, showing that the MLPM model achieves the best tumour prediction precision.","A Survey on an Effective Identification and Analysis for Brain Tumour Diagnosis using Machine  \nLearning Technique  \nPadma Parshapa1, P. Ithaya Rani2  \n1Research scholar, Computer Science and Engineering Department,  \nKoneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur district, Andhra Pradesh  \n[Email: padma.parshapu@gmail.com](Email: padma.parshapu@gmail.com)  \n2Associate professor, Computer Science and Engineering Department,  \nKoneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur district, Andhra Pradesh  \nEmail: [drpithayarani@kluniversity.in](drpithayarani@kluniversity.in)  \nAbstract: The hottest issue in medicine is image analysis. It has drawn a lot of researchers since it can effectively assess the severity of the condition and forecast the outcome. The noise trimming outcomes, on the other hand, have reduced with more complex trained images, which has tended to result in a lower prediction exactness score. So, a novel Machine Learning prediction framework has been built in this present study. This work also tries to predict brain tumours and evaluate their severity using MRI brain scans. Using the boosting function, the best results for error pruning are produced. The Proposed Solution function was then used to successfully complete the feature analysis and tumour prediction operations. The intended framework is evaluated in the Python environment, and a comparative analysis is performed to examine the prediction improvement score. It was discovered that an original MLPM model had the best tumour prediction precision.  \nKeywords: Brain tumour prediction; feature analysis; severity analysis; Machine learning; prediction accuracy.  \nI. INTRODUCTION  \nIn a human biological system, the brain tumour is considered a harmful disease category [1]. Hence, the early tumour diagnosis framework is a major concern in recovering human lives with proper treatment procedures [2] . Several medical analysis tools exist for these diagnosis systems [3] . However, those tools are high in cost also that is not suitable for predicting all tumour types [4]. Considering these drawbacks, intelligent models have been introduced for the disease prediction problem, which functioned as a neural model [5]. The neural framework process without the optimum layer is defined as machine learning (ML)  \n[6] . Also, the neural models processed with optimal layers for the tuned prediction outcome are termed deep learning (DL) networks [7] . However, the neural models have needed more periods to train the system [8] . Furthermore, the imaging analysis was introduced to the medical framework for the finest visualization results [9] . Some imaging schemes have required more image features to train the system that has maximized the complexity score of the imagining system [10] . A brain tumour might start in the brain cells (as depicted in figure-1) or it can start somewhere else and spread to the brain. As the tumour grows, it places pressure on and alters the function of nearby brain tissue, resulting in headaches, nausea, and balance issues.  \nFig-1 Brain Tumor representation-1  \nA brain tumour is a grouping of abnormal brain cells. There are numerous types of brain tumours. Some brain tumours are noncancerous (harmless), whereas others are cancerous (malignant). Brain tumours can start in the brain (primary brain tumour) or spread to the brain from other parts of the body (metastatic brain tumor) .  \nFig-2 Brain tumor representation-2 and Overall representation  \nMoreover, the critical contribution steps of the designed prediction system are described as follows,  \nTable-1 Symptoms of Brain tumor  \n\n| Symptoms | Types of Tumors |\n| --- | --- |\n| A new migraine attack or a change in headache pattern | Gliomas. |\n| Headaches that worsen and grow more frequent over time | Meningiomas. |\n| The reason of nausea or vomiting is unknown. | Acoustic neuromas |\n| Vision difficulties such as decreased vision, double vision, or peripheral vision loss | ","cbCaidl7C40W9JYU","https://ap.wps.com/l/cbCaidl7C40W9JYU","pdf",792980,1,11,"English","en",105,"# Introduction\n## Brain tumour overview and symptoms\n## Classical machine learning techniques for diagnosis\n## Proposed machine learning framework and pipeline\n## Evaluation metrics","[{\"question\":\"Why is image analysis important for brain tumour diagnosis?\",\"answer\":\"Image analysis helps assess condition severity and forecast outcomes, enabling more effective early diagnosis decisions.\"},{\"question\":\"What problem does the proposed framework address regarding noise trimming and accuracy?\",\"answer\":\"More complex trained images can weaken noise-trimming outcomes, leading to reduced prediction exactness; the framework improves prediction using a novel ML approach.\"},{\"question\":\"How is tumour prediction performed and evaluated in the proposed study?\",\"answer\":\"MRI brain scans are used as inputs, preprocessing removes noise features, and feature analysis supports tumour region detection by matching test and trained healthy features; results are evaluated using metrics such as prediction accuracy, recall, and precision.\"}]","A Survey on an Effective Identification and Analysis for Brain Tumour Diagnosis using Machine Learning Technique | PDF",1785933524,28,{"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":87,"head_meta":89,"extra_data":91,"updated_unix":28},"a-survey-on-an-effective-identification-and-analysis-for-brain-tumour-diagnosis-using-machine-learning-technique","",{"@graph":36,"@context":86},[37,54,69],{"@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/healthcare/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/a-survey-on-an-effective-identification-and-analysis-for-brain-tumour-diagnosis-using-machine-learning-technique/126588/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-22","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"Why is image analysis important for brain tumour diagnosis?","Question",{"text":76,"@type":77},"Image analysis helps assess condition severity and forecast outcomes, enabling more effective early diagnosis decisions.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What problem does the proposed framework address regarding noise trimming and accuracy?",{"text":81,"@type":77},"More complex trained images can weaken noise-trimming outcomes, leading to reduced prediction exactness; the framework improves prediction using a novel ML approach.",{"name":83,"@type":74,"acceptedAnswer":84},"How is tumour prediction performed and evaluated in the proposed study?",{"text":85,"@type":77},"MRI brain scans are used as inputs, preprocessing removes noise features, and feature analysis supports tumour region detection by matching test and trained healthy features; results are evaluated using metrics such as prediction accuracy, recall, and precision.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,119,124,129,132,136],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":117,"slug":118},40,"healthcare",{"id":120,"doc_module":4,"doc_module_name":46,"category_name":121,"show_sort_weight":122,"slug":123},8,"Research & Report",30,"research-report",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":46,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":46,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]