[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127326-en":3,"doc-seo-127326-105":29,"detail-sidebar-cat-0-en-105":90},{"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":11,"language":21,"language_code":22,"site_id":23,"html_lang":22,"table_of_contents":24,"faqs":25,"seo_title":26,"seo_description":14,"update_tm":27,"read_time":28},127326,962085570644,"Evangeline","https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d",8,"Research & Report","Breast Cancer Detection Using a Syrian Biomarkers Dataset and Machine Learning Algorithms - Abstract","Breast cancer is the most common cancer affecting women worldwide, and advances in spectral blood-analysis techniques have enabled the use of biomarkers for classification, diagnosis, and prediction of malignant tumors. Machine learning methods are increasingly applied to biomarker data for breast cancer detection. The research builds a Syrian biomarker dataset from hospitals and laboratories, then evaluates feedforward neural networks (FNN), support vector machine (SVM), and k-nearest neighbors (K-NN). Results show FNN achieves the best accuracy (95%), with sensitivity 95.2% and specificity 94.7%, outperforming SVM accuracy 92.5% and specificity 95.2%.","Breast Cancer Detection Using a Syrian Biomarkers Dataset and  \nMachine Learning Algorithms  \nReceived: 10/3/2023  \nAccepted: 29/5/2023  \nCopyright: Damascus University- Syria, The authors retain the copyright under a  \nCC BY-NC-SA  \nHiba Allah Essa*1 Mhd Firas Alhinawwi2  \n*1. Engineer, Department of Biomedical Engineering, Faculty of Mechanical and Electrical Engineering, Damascus University.  \n[hiba.essa@damascusuniversity.edu.sy](hiba.essa@damascusuniversity.edu.sy)  \n2. Professor, Department of Biomedical Engineering, Faculty of Mechanical and Electrical Engineering, Damascus University.  \n[hiba.essa@damascusuniversity.edu.sy](hiba.essa@damascusuniversity.edu.sy)  \nAbstract:  \nBreast cancer is the most common type of cancer that affects women worldwide. The development of spectral analysis techniques and devices for blood analysis enhanced the use of biomarkers and what they can help in classifying, diagnosing and predicting the presence of cancers and malignant tumors. Recently, machine learning algorithms have been used with biomarkers in the diagnosis and detection of breast cancer. This research aims to create a Syrian dataset of biomarkers from Syrian hospitals and laboratories. The Syrian dataset is used to detect breast cancer using feedforward neural networks (FNN), support vector machine (SVM) and the knearest neighbours algorithm (K-NN) . The test performance showed that the FNN gives the best accuracy with a value of 95%, a sensitivity of 95.2% anda specificity of 94.7% . The SVM model gave an accuracy of 92.5% and a specificity of 95.2% . Compared to related work, the Syrian dataset shows the efficiency of obtained biomarkers in detecting breast cancer.  \nKeywords: Breast cancer; feed-forward neural networks; biomarkers; machine learning.  \nكشف سرطان الثدي باستخداممجموعة بيانات سورية من المؤشرات الحيوية وخوارزميات تعلم  \nالآلة  \nهبة الله عيسى* 1 محمد فراس الحناوي2  \n* 1. مهندسة، قسم الهندسة الطبية، كلية الهندسة الميكانيكية والكهربائية، جامعة دمشق.  \n[hiba.essa@damascusuniversity.edu.sy](hiba.essa@damascusuniversity.edu.sy)  \n2. أستاذ في قسم الهندسة الطبية، كلية الهندسة الميكانيكية والكهربائية، جامعة دمشق.  \n[mhdfiras.alhinnawi@damascusuniversity.edu.Sy](mhdfiras.alhinnawi@damascusuniversity.edu.Sy)  \nالملخص :  \nسرطان الثدي هو أكثر أنواع السرطانات شيوواا التيي يبيول النسيا فيي جمييء أنعيا العيالم.  \nيطور يقنيات التعلول الطيفي وأجهزة يعلول مركبات الدم ايجه بالعلم إلى العمل الى مفهوم  \nالمؤشييرات العوو يية ومييا نمكييع أن يسييااد فييي يبيينيب ويشييديا والتنبييؤ وجييود السييرطاناتوا لأورام ا لدبوثيية بونواهييا .مؤخرا يييم اتاتميياد الييى خوارزميييات يعلييم ا ليية تسييتددام المؤشييراتالعوو ة في يشديا سرطان الثدي واكتشافه. يهدف هياا البعي إليى إنشيا مجمواية يانياتسيييورة ميييع المستشيييخيات والمديييا ر السيييورة والتيييي يعتميييد اليييى المؤشيييرات العوو ييية المتعيييارف  \nالوها مع قبل الأطبا المدتبوع .  \nثانيا، التوكد مع قدرة هيا المؤشيرات اليى كشيط سيرطان الثيدي ميع خيام اسيتددام الشيبكاتالعبييييبونية ذات اتنتشييييار الأميييياميFNN ونمييييوذجي يعلييييم ليييية همييييا ليييية متجييييه الييييدامSVM وخوارزميية الجويران الأقير NN-K فييي يبينيب العياتت السييليمة والسيرطانية منهيا . أ هييرتنتائج اتختبار أن الشبكة العببونية FNN يعطي أفضل دقية بييمية %59وحساسيية%5952 ونوعيييية%5.59. ونميييا أ هييير نميييوذ SVM دقييية %5259 ونوعيييية %5952. بالمقارنييية ميييءالأبعيييييياى الأخيييييير ، يظهيييييير مجموايييييية البيانييييييات السييييييورة مييييييد كفييييييا ة المؤشييييييرات العوو يييييية  \nالمستعبلة مع التعالول الطبية في كشط سرطان الثدي .  \nالكلمااات الماتاةيااة: سييرطان الثييدي، الشييبكات العبييبونية ذات التاانيية الأمامييية، المؤشييرات  \nالعوو ة، يعلم ا لة.  \nتاريخ الإيداع: 2123/3/11  \nتاريخ القبول: 2123/9/25  \nةقوق النشر: جامعة دمشق–سورة، نعتفظ المؤلفونبعقوق النشر بموجل -CC BY  \nNC-SA  \n(ng/mL), adiponectin (µg/mL), resistin (ng/mL), and monocyte chemoattractant protein-1 (MCP-1)(pg/dL) . This database is available on the UCI Machine Learning Repository. In the same research, SVM models using Resistin, BMI, glucose, and ag","cbCaiclkOwKqIlT3","https://ap.wps.com/l/cbCaiclkOwKqIlT3","pdf",1455812,1,"English","en",105,"# Abstract\n## Data creation from Syrian hospitals and laboratories\n## Machine learning models: FNN, SVM, K-NN\n## Evaluation metrics and results","[{\"question\":\"What is the main goal of the study?\",\"answer\":\"To create a Syrian biomarker dataset and use machine learning algorithms to detect breast cancer.\"},{\"question\":\"Which machine learning models are evaluated?\",\"answer\":\"Feedforward neural networks (FNN), support vector machine (SVM), and k-nearest neighbors (K-NN).\"},{\"question\":\"How does FNN perform compared with SVM?\",\"answer\":\"FNN achieves the best accuracy of 95% with sensitivity 95.2% and specificity 94.7%, while SVM reaches 92.5% accuracy with specificity 95.2%.\"}]","Breast Cancer Detection Using a Syrian Biomarkers Dataset and Machine Learning Algorithms - Abstract | PDF",1785938311,20,{"code":4,"msg":30,"data":31},"ok",{"site_id":23,"language":22,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":27},"breast-cancer-detection-using-a-syrian-biomarkers-dataset-and-machine-learning-algorithms-abstract","",{"@graph":35,"@context":84},[36,53,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/breast-cancer-detection-using-a-syrian-biomarkers-dataset-and-machine-learning-algorithms-abstract/127326/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":22,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"What is the main goal of the study?","Question",{"text":74,"@type":75},"To create a Syrian biomarker dataset and use machine learning algorithms to detect breast cancer.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"Which machine learning models are evaluated?",{"text":79,"@type":75},"Feedforward neural networks (FNN), support vector machine (SVM), and k-nearest neighbors (K-NN).",{"name":81,"@type":72,"acceptedAnswer":82},"How does FNN perform compared with SVM?",{"text":83,"@type":75},"FNN achieves the best accuracy of 95% with sensitivity 95.2% and specificity 94.7%, while SVM reaches 92.5% accuracy with specificity 95.2%.","https://schema.org",{"og:url":51,"og:type":86,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":88,"canonical":51},"index,follow",{"doc_id":7,"site_id":23},{"code":4,"msg":5,"data":91},[92,96,100,104,109,114,119,122,126,129,133],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":93,"show_sort_weight":94,"slug":95},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":97,"show_sort_weight":98,"slug":99},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":45,"category_name":101,"show_sort_weight":102,"slug":103},"Exam",70,"exam",{"id":105,"doc_module":4,"doc_module_name":45,"category_name":106,"show_sort_weight":107,"slug":108},5,"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":45,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":45,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":45,"category_name":124,"show_sort_weight":28,"slug":125},9,"Religion & Spirituality","religion-spirituality",{"id":28,"doc_module":4,"doc_module_name":45,"category_name":127,"show_sort_weight":28,"slug":128},"World Cup","world-cup",{"id":130,"doc_module":4,"doc_module_name":45,"category_name":131,"show_sort_weight":130,"slug":132},10,"Lifestyle","lifestyle",{"id":134,"doc_module":4,"doc_module_name":45,"category_name":135,"show_sort_weight":105,"slug":136},19,"General","general"]