[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123947-en":3,"doc-seo-123947-105":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},123947,5909877438554,"Maeve","https://ap-avatar.wpscdn.com/avatar/5600025385ad2bf12a7?_k=1778553567797529272",8,"Research & Report","Detection of Breast Cancer through the Analysis of Radiographic Images Using Machine Learning: A Systematic Review","Breast cancer poses a serious risk due to late detection, which may stem from human error in interpreting radiographic images or from delays in clinical settings. Machine learning is proposed as a support tool for radiologists to reduce false diagnostic rates and improve consistency. Evidence from the research process highlights both benefits and limitations of ML, while indicating insufficient clinical testing and methodological detail, resulting in inconclusive effectiveness.","JOE International Journal of  \nOnline and Biomedical Engineering  \n[Onli](Online-Journals.org)[ne-Jo](Online-Journals.org)[urnals](Online-Journals.org)[.org](Online-Journals.org)  \niJOE | eISSN: 2626-8493 | Vol. 20 No. 5 (2024) |   \n[https://doi.org/10.3991/ijoe.v20i05.46791](https://doi.org/10.3991/ijoe.v20i05.46791)  \nPAPER  \nDetection of Breast Cancer through the Analysis of Radiographic Images Using Machine Learning: A Systematic Review  \nKristell Yukie Jimenez Ayala(􀀍)  \nUniversidad Tecnológica del Perú, Lima, Peru  \n[u19314997@utp.edu.pe](u19314997@utp.edu.pe)  \nABSTRACT  \nBreast cancer is an illness that affects many women and can cause even death; this is a case of not being detected on time, which could be due to a human error during the analysis of radiographic images or not going on time in a health center. For this, using machine learning (ML) to analyze radiographic images is proposed as a support tool for radiologists aiming to reduce false diagnostic rates. While researching information, it was detected that this technology has many benefits in the health area; however, it also has limitations or disadvantages. The importance of this paper is to demonstrate that there are not enough clinical tests nor details about the methodologies that were used; there should be more to assert that ML is defined at the moment of making a diagnosis, which generates no conclusive results regarding effectiveness and therefore creates mistrust in doctors, and some people might rather use deep learning (DL) for its application in the detection of breast cancer because DL has more practical tests and fewer limitations than machine learning.  \nKEYWORDS  \nmachine learning (ML), medicine, breast cancer, detection, systematic review, cancer diagnostics, cancer prognosis, mammography  \n1 INTRODUCTION  \nBreast cancer is women’s most frequently diagnosed cancer and rapidly grows [1] . It is the fifth most common cause of death [2], accounting for approximately 685,000 deaths a year [3] . One in eight women develops it in her lifetime [4] . Unfortunately, late detection of breast cancer leads to a diminished quality of life and is the primary cause of death. At least 70% of women are diagnosed with cancer in its advanced stages, negatively impacting survival rates [5] .  \nCancer identification outcomes rely on human interpretation, resulting in false positives or negatives. This generates anxiety and unnecessary patient concerns,  \nJimenez Ayala, K.Y. (2024) . Detection of Breast Cancer through the Analysis of Radiographic Images Using Machine Learning: A Systematic Review.  \nInternational Journal of Online and Biomedical Engineering (iJOE), 20(5), pp. 120–132. [https://doi.org/10.3991/ijoe.v20i05.46791](https://doi.org/10.3991/ijoe.v20i05.46791)[ ](https://doi.org/10.3991/ijoe.v20i05.46791)[Article submitted 2023-10-16. Revision uploaded 2023-11-22. Final acceptance 2023-11-25.](Article submitted 2023-10-16. Revision uploaded 2023-11-22. Final acceptance 2023-11-25.)  \n© 2024 by the authors of this article. Published under CC-BY.  \n120 International Journal of Online and Biomedical Engineering (iJOE) iJOE | Vol. 20 No. 5 (2024)  \nDetection of Breast Cancer through the Analysis of Radiographic Images Using Machine Learning: A Systematic Review  \nsometimes portraying the cancer as more aggressive and rapidly progressing [6] . Overdiagnosis and excessive testing have also made patients symptomatic [7] .  \nGiven the issues above, delayed detection of this disease poses a problem, emphasizing the importance of early breast cancer diagnosis. Early detection is crucial, as disease progression complicates treatment [8] . Diagnosing it in its early stages can reduce associated mortality [9] and increase patient survival rates by 50%[1]. Early detection offers the best opportunity for effective and gentle treatments [9], making cures more achievable [10] .  \nSpecialists usually conduct inspections, or mammograms, to improve early detection. However,","cbCainpSIGz4n1Ji","https://ap.wps.com/l/cbCainpSIGz4n1Ji","pdf",606456,1,13,"English","en",105,"# Introduction\n## Breast cancer burden and the need for early detection\n## Role of radiographic interpretation and diagnostic errors\n# Proposed solution and motivation\n## ML as second-opinion support","[{\"question\":\"Why is early breast cancer detection emphasized in the document?\",\"answer\":\"Late detection diminishes quality of life and increases mortality risk. Early diagnosis enables more effective and less burdensome treatments and improves survival chances.\"},{\"question\":\"How does the document propose machine learning to help with breast cancer detection?\",\"answer\":\"Machine learning is presented as an image-analysis support tool for radiologists, aiming to reduce false positives and negatives and provide more consistent interpretation than purely human assessment.\"},{\"question\":\"What limitations of machine learning are discussed?\",\"answer\":\"The document notes a lack of enough clinical tests and insufficient methodological detail in existing evidence, leading to non-conclusive results and reduced confidence in effectiveness.\"}]","Detection of Breast Cancer through the Analysis of Radiographic Images Using Machine Learning: A Systematic Review | PDF",1785819382,33,{"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},"detection-of-breast-cancer-through-the-analysis-of-radiographic-images-using-machine-learning-a-systematic-review","",{"@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/detection-of-breast-cancer-through-the-analysis-of-radiographic-images-using-machine-learning-a-systematic-review/123947/",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},"Why is early breast cancer detection emphasized in the document?","Question",{"text":75,"@type":76},"Late detection diminishes quality of life and increases mortality risk. Early diagnosis enables more effective and less burdensome treatments and improves survival chances.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does the document propose machine learning to help with breast cancer detection?",{"text":80,"@type":76},"Machine learning is presented as an image-analysis support tool for radiologists, aiming to reduce false positives and negatives and provide more consistent interpretation than purely human assessment.",{"name":82,"@type":73,"acceptedAnswer":83},"What limitations of machine learning are discussed?",{"text":84,"@type":76},"The document notes a lack of enough clinical tests and insufficient methodological detail in existing evidence, leading to non-conclusive results and reduced confidence in effectiveness.","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"]