[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121322-en":3,"doc-seo-121322-105":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},121322,1099514067438,"River Wang","https://ap-avatar.wpscdn.com/avatar/100002539ee87300030?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780474512215547542",7,"Healthcare","Migraine triggers, phases, and classification using machine learning models","Migraine triggers and distinct clinical phases remain frequently under-recognized and misdiagnosed, contributing to delayed or inadequate care. This study reviews established triggers and phases, then classifies migraine types based on compiled patient-reported clinical study data. Multiple machine learning models—including logistic regression, support vector machine, random forest, and artificial neural networks—are trained for diagnostic classification and evaluated using performance verification, selective sampling, and tuning. Results show strong precision and accuracy, with the artificial neural network demonstrating the most reliable performance across sampling strategies.","TYPE Original Research PUBLISHED 09 May 2025  \nDOI 10. 3389/fneur.2025.1555215  \nOPEN ACCESS  \nEDITED BY  \nXiangmin Fan,  \nInstitute of Software, Chinese Academy of Sciences (CAS), China  \nREVIEWED BY  \nLanfranco Pellesi,  \nUniversity of Southern Denmark, Denmark Alicia Gonzalez-Martinez,  \nPrincess University Hospital, Spain  \n*CORRESPONDENCE  \nAjit Reddy  \n [ajitk_reddy@yahoo.com](ajitk_reddy@yahoo.com)  \nRECEIVED 03 January 2025  \nACCEPTED 07 April 2025  \nPUBLISHED 09 May 2025  \nCITATION  \nReddy A and Reddy A (2025) Migraine triggers, phases, and classification using machine learning models. Front. Neurol. 16:1555215 .  \ndoi: 10.3389/fneur.2025.1555215  \nCOPYRIGHT  \n© 2025 Reddy and Reddy. This is an  \nopen-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.  \nMigraine triggers, phases, and classification using machine learning models  \nAnusha Reddy1 and Ajit Reddy  2*  \n1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States, 2 Independent Researcher, Monmouth County, NJ, United States  \nBackground: In many countries, patients with headache disorders such as migraine remain under-recognized and under-diagnosed. Patients a􀀀ected by these disorders are often unaware of the seriousness of their conditions, as headaches are neither fatal nor contagious. In many cases, patients with migraine are often misdiagnosed as regular headaches.  \nMethods: In this article, we present a study on migraine, covering known triggers, di􀀀erent phases, classification of migraine into di􀀀erent types based on clinical studies, and the use of various machine learning algorithms such as logistic regression (LR), support vector machine (SVM), random forest (RF), and artificial neural network (ANN) to learn and classify di􀀀erent migraine types. This study will only consider using these methods for diagnostic purposes. Models based on these algorithms are then trained using the dataset, which includes a compilation of the types of migraine experienced by various patients. These models are then used to classify the types of migraines, and the results are analyzed.  \nResults: The results of the machine learning models trained on the dataset are verified for their performance. The results are further evaluated by selective sampling and tuning, and improved performance is observed. The precision and accuracy obtained by the support vector machine and artificial neural network are 91% compared to logistic regression (90%) and random forest (87%) . These models are run with the dataset without optimal tuning across the entire dataset for di􀀀erent migraine types; which is further improved with selective sampling and optimal tuning. These results indicate that the discussed models are relatively good and can be used with high precision and accuracy for diagnosing di􀀀erent types of migraine.  \nConclusion: Our study presents a realistic assessment of promising models that are dependable in aiding physicians. The study shows the performance of various models based on the classification metrics computed for each model. It is evident from the results that the artificial neural network (ANN) performs better, irrespective of the sampling techniques used. With these machine learning models, types of migraines can be classified with high accuracy and reliability, enabling physicians to make timely clinical diagnoses of patients.  \nKEYWORDS  \nmigraine triggers, migraine phases, migraine types, logistic regression, support vector machine, random forest, neural networks  \nFrontiersin Neurology 01 [frontiersin.org](frontiersin.org)  \nIntroduction  \nBackground  \nMigraine is a severe and d","cbCaikrnIXr3F7uQ","https://ap.wps.com/l/cbCaikrnIXr3F7uQ","pdf",877545,1,11,"English","en",105,"# Introduction\n## Background\n# Methods\n## Machine learning model training and classification\n# Results\n## Performance verification, selective sampling, and tuning\n# Conclusion","[{\"question\":\"Why do migraine disorders often remain under-recognized or misdiagnosed?\",\"answer\":\"Many patients are unaware of the seriousness of migraine because headaches are not typically fatal or contagious. Migraine can also be mistaken for regular headaches, leading to under-diagnosis.\"},{\"question\":\"Which machine learning algorithms are used to classify migraine types?\",\"answer\":\"The study uses logistic regression, support vector machine, random forest, and artificial neural networks for diagnostic classification of migraine types.\"},{\"question\":\"What improvements were achieved through selective sampling and optimal tuning?\",\"answer\":\"Model performance was verified and further evaluated using selective sampling and tuning, leading to improved metrics across different migraine types.\"}]","Migraine triggers, phases, and classification using machine learning models | PDF",1785735066,28,{"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":86,"head_meta":88,"extra_data":90,"updated_unix":28},"migraine-triggers-phases-and-classification-using-machine-learning-models","",{"@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/healthcare/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/migraine-triggers-phases-and-classification-using-machine-learning-models/121322/",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","2026-08-03",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 do migraine disorders often remain under-recognized or misdiagnosed?","Question",{"text":75,"@type":76},"Many patients are unaware of the seriousness of migraine because headaches are not typically fatal or contagious. Migraine can also be mistaken for regular headaches, leading to under-diagnosis.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which machine learning algorithms are used to classify migraine types?",{"text":80,"@type":76},"The study uses logistic regression, support vector machine, random forest, and artificial neural networks for diagnostic classification of migraine types.",{"name":82,"@type":73,"acceptedAnswer":83},"What improvements were achieved through selective sampling and optimal tuning?",{"text":84,"@type":76},"Model performance was verified and further evaluated using selective sampling and tuning, leading to improved metrics across different migraine types.","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},[93,97,101,105,110,115,118,123,128,131,135],{"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":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":116,"slug":117},40,"healthcare",{"id":119,"doc_module":4,"doc_module_name":46,"category_name":120,"show_sort_weight":121,"slug":122},8,"Research & Report",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"]