[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121096-en":3,"doc-seo-121096-105":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},121096,8796095461564,"Liam","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",7,"Healthcare","A New Hybrid Method to Detect Risk of Gastric Cancer using Machine Learning Techniques - Research Paper","Machine learning supports healthcare by analyzing large patient datasets, enabling disease prediction, early warning detection, and improved clinical decision-making. Gastric cancer originates in stomach lining cells and is among the most common cancers globally, making early risk detection crucial for patient outcomes. This paper proposes a new hybrid machine-learning approach that combines multi-layer perceptron and support vector machine. The model is evaluated against traditional methods and achieves 98% accuracy, offering a non-invasive way to assess gastric cancer risk and clarify relationships with H. pylori infection and lifestyle factors.","Journal of Artificial Intelligence and Data Mining (JAIDM), Vol. 11, No. 4, 2023, 505-515.  \n\n| \u003Cbr>Shahrood University of\u003Cbr>Technology | \u003Cbr>Journal of Artificial Intelligence and Data Mining (JAIDM)\u003Cbr>Journal homepage: [http://jad.shahroodut.ac.ir](http://jad.shahroodut.ac.ir)\u003Cbr> |\n| --- | --- |\n| Research paper\u003Cbr>A New Hybrid Method to Detect Risk of Gastric Cancer using Machine\u003Cbr>Learning Techniques\u003Cbr>Ali Zahmatkesh Zakariaee1, Hossein Sadr2* and Mohammad Reza Yamaghani3\u003Cbr>1. Department of Computer Engineering, Rahbord Shomal Institute of Higher Education, Rasht, Iran.\u003Cbr>2. Department of health Informatics, Guilan Road Trauma Research Center, Trauma institute, Guilan University of medical sciences, Rasht, Iran.\u003Cbr>3. Department of Computer Engineering, Faculty of Engineering, Lahijan Branch, Islamic Azad University, Lahijan, Iran. |  |\n\nArticle Info  \nArticle History:  \nReceived 18 July 2023  \nRevised 05 September 2023  \nAccepted 15 October 2023  \n DOI:10.22044/jadm.2023.13377.2464   \nKeywords:  \nArtificial Intelligence, Machine Learning, Gastric cancer, Hybrid Method, Neural Network.  \n\n| *Corresponding [Sadr@qiau.ac.ir](Sadr@qiau.ac.ir) (H. Sdar). | author: |\n| --- | --- |\n\nAbstract  \nMachine learning (ML) is a popular tool in healthcare while it can help to analyze large amounts of patient data such as medical records, predict diseases, and identify early signs of cancer. Gastric cancer starts in the cells lining the stomach, and is known as the 5th most common cancer worldwide. Therefore, predicting the survival of patients, checking their health status, and detecting their risk of gastric cancer in the early stages can be very beneficial. Surprisingly, with the help of machine learning methods, this can be possible without the need for any invasive methods that can be useful for both patients and physicians in making informed decisions. Accordingly, a new hybrid machine learning-based method for detecting the risk of gastric cancer is proposed in this paper. The proposed model is compared with the traditional methods, and based on the empirical results, not only the proposed method outperform existing methods with an accuracy of 98% but also gastric cancer can be one of the most important consequences of H. pylori infection. Additionally, it can be concluded that lifestyle and dietary factors can heighten the risk of gastric cancer, especially among individuals who frequently consume fried foods and suffer from chronic atrophic gastritis and stomach ulcers. This risk is further exacerbated in individuals with limited fruit and vegetable intake and high salt consumption.  \n1. Introduction  \nMany diseases have affected humanity throughout history and have taken many lives. Gastric cancer is a prevalent malignancy with a high incidence and mortality rate worldwide. The gastric cancer risk factors vary by country, and are associated with urbanization and economic development. Diagnosing gastric cancer is difficult, with only about 10% of people diagnosed while still in the early stages. Studies indicate that gastric cancer (GC) ranks fifth among the most common cancers worldwide, and is considered a multifactorial and dangerous disease [1] . This factor is responsible for one-third of cancer-related deaths, and is considered the third leading cause of cancer-related fatalities [2] . In Iran, cancer is the second leading  \ncause of death after heart disease [3] . Moreover, the 5-year survival rate in Iran is estimated at less than 25%[4] .  \nSurgery is considered as the primary treatment of gastric cancer. However, due to the lack of clear symptoms in the early stages, and because many of the initial symptoms mimic indigestion, patients often receive treatment in the advanced stages of cancer. This significantly impacts the survival rate, reducing it by up to 50% [5-7] . Hence, the utilization of artificial intelligence and machine learning mining methods is crucial for investigating the characteristics of gastric ","cbCaiigrEluVcnZy","https://ap.wps.com/l/cbCaiigrEluVcnZy","pdf",799516,1,11,"English","en",105,"# Article History\n## Received, Revised, Accepted\n# Abstract\n## Purpose and Proposed Hybrid Model\n# Introduction\n## Burden and Risk Factors of Gastric Cancer\n## Challenges in Early Diagnosis\n# Methods\n## Model Design (MLP + SVM)\n## Dataset and Risk Classes","[{\"question\":\"What hybrid machine learning method is proposed for gastric cancer risk detection?\",\"answer\":\"The study proposes a hybrid model that combines Multi-Layer Perceptron (MLP) and Support Vector Machine (SVM) to improve prediction performance.\"},{\"question\":\"How is the proposed model evaluated and what accuracy is reported?\",\"answer\":\"The model is compared with traditional methods using empirical results, showing an accuracy of 98%.\"},{\"question\":\"Which factors are highlighted as associated with gastric cancer risk?\",\"answer\":\"The paper points to a significant link between H. pylori infection and gastric cancer, and suggests that lifestyle and dietary patterns can heighten risk.\"}]","A New Hybrid Method to Detect Risk of Gastric Cancer using Machine Learning Techniques - Research Paper | PDF",1785733706,28,{"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},"a-new-hybrid-method-to-detect-risk-of-gastric-cancer-using-machine-learning-techniques-research-paper","",{"@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/a-new-hybrid-method-to-detect-risk-of-gastric-cancer-using-machine-learning-techniques-research-paper/121096/",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},"What hybrid machine learning method is proposed for gastric cancer risk detection?","Question",{"text":75,"@type":76},"The study proposes a hybrid model that combines Multi-Layer Perceptron (MLP) and Support Vector Machine (SVM) to improve prediction performance.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is the proposed model evaluated and what accuracy is reported?",{"text":80,"@type":76},"The model is compared with traditional methods using empirical results, showing an accuracy of 98%.",{"name":82,"@type":73,"acceptedAnswer":83},"Which factors are highlighted as associated with gastric cancer risk?",{"text":84,"@type":76},"The paper points to a significant link between H. pylori infection and gastric cancer, and suggests that lifestyle and dietary patterns can heighten risk.","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"]