[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-119453-en":3,"doc-seo-119453-105":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":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},119453,1374391974468,"Eden","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","Machine Learning-Based Breast Cancer Diagnosis - Master of Science Thesis","This thesis presents a machine learning approach for breast cancer diagnosis, addressing limitations of traditional diagnostic workflows through data preprocessing and model-driven classification. It reviews diagnostic imaging techniques and prior computer-aided detection systems, then develops and compares convolutional neural network, random forest, and logistic regression approaches. The work details dataset preparation steps such as resizing, normalization, and augmentation, and evaluates performance using established metrics to assess accuracy and generalizability for early detection support.","CALIFORNIA STATE UNIVERSITY, NORTHRIDGE  \nMACHINE LEARNING-BASED BREAST CANCER DIAGNOSIS  \nA thesis submitted in partial fulfillment of the Requirements for the degree of  \nMaster of Science in Computer Science  \nBy  \nJanani Naga Sai Pravallika Gogineni  \nAUGUST 2024  \nThe thesis of Janani Naga Sai Pravallika Gogineni is approved:  \nMaryam Jalali,Ph.D. Date  \nRobert D Mcllhenny, Ph.D. Date  \nAdam B Kaplan, Ph.D., Chair Date  \nCalifornia State University, Northridge  \nTABLE OF CONTENTS  \nSignature Page ...........................................................................................................................ii  \nTable of Contents ..................................................................................................................... iii  \nList of [figures............................................................................................................................vi](figures............................................................................................................................vi)  \n[Abstract ...............................](Abstract ...............................).....................................................................................................vii  \nChapter 1: Introduction .............................................................................................................. 1  \n1.1 Background of the research ............................................................................................. 1  \n1.2 Aim...................................................................................................................................2  \n1.3 Objectives ........................................................................................................................2  \n1.4 Research Questions ..........................................................................................................2  \n1.5 Importance of Early Detection .........................................................................................2  \n1.6 Problem Domain ..............................................................................................................3  \n1.7 Challenges in Diagnosis...................................................................................................4  \n1.8 Role of Ultrasound Imaging.............................................................................................4  \n1.9 Analytical Methodology................................................................................................... 5  \nChapter 2: Literature Review .....................................................................................................7  \n2.1 Comparison of Diagnostic Imaging Techniques ..............................................................7  \n2.2 Advancements in Computer-Aided Detection (CAD) Systems .......................................9  \n2.2.2Modern CAD Systems Using Deep Learning............................................................9  \n2.3 Deep Learning Models for Breast Cancer Detection ..................................................... 10  \n2.3.1 VGG-16................................................................................................................... 10  \n2.3.2 ResNet ..................................................................................................................... 10  \n2.3.3 Inception ................................................................................................................. 11  \n2.3.4 DenseNet ................................................................................................................. 11  \n2.4 Machine Learning Approaches ...................................................................................... 11  \n2.5 Challenges with Data and Model Training .................................................................... 12  \n2.5.1 Need for Large, Annotated Datasets ................................","cbCaiswONkbg7Pwa","https://ap.wps.com/l/cbCaiswONkbg7Pwa","pdf",2098338,1,71,"English","en",105,"# Chapter 1: Introduction\n## Background of the research\n## Aim\n## Objectives\n## Research Questions\n## Importance of Early Detection\n## Problem Domain\n## Challenges in Diagnosis\n## Role of Ultrasound Imaging\n## Analytical Methodology\n# Chapter 2: Literature Review\n## Comparison of Diagnostic Imaging Techniques\n## Advancements in Computer-Aided Detection (CAD) Systems\n## Deep Learning Models for Breast Cancer Detection\n## Machine Learning Approaches\n## Challenges with Data and Model Training\n## Evaluation Metrics and Performance\n## Summary of Literature Reviews\n# Chapter 3: Background\n## Dataset Description\n## Data Preprocessing\n## CNN Model Architecture\n## Random Forest Model\n## Logistic Regression\n# Chapter 4: Methodology\n## Experimental Setup","[{\"question\":\"What is the main goal of the thesis on breast cancer diagnosis?\",\"answer\":\"The thesis aims to build and compare machine learning methods to support breast cancer diagnosis using prepared imaging data and model-based classification.\"},{\"question\":\"Which techniques are reviewed in the literature review?\",\"answer\":\"It reviews diagnostic imaging techniques, computer-aided detection systems, and deep learning models such as VGG-16, ResNet, Inception, and DenseNet, along with other machine learning approaches and training challenges.\"},{\"question\":\"How is the dataset prepared before training the models?\",\"answer\":\"The thesis describes preprocessing steps including resizing, normalization, and data augmentation to improve model learning and robustness.\"}]","Machine Learning-Based Breast Cancer Diagnosis - Master of Science Thesis | PDF",1785724355,179,{"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},"machine-learning-based-breast-cancer-diagnosis-master-of-science-thesis","",{"@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/machine-learning-based-breast-cancer-diagnosis-master-of-science-thesis/119453/",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":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the main goal of the thesis on breast cancer diagnosis?","Question",{"text":75,"@type":76},"The thesis aims to build and compare machine learning methods to support breast cancer diagnosis using prepared imaging data and model-based classification.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which techniques are reviewed in the literature review?",{"text":80,"@type":76},"It reviews diagnostic imaging techniques, computer-aided detection systems, and deep learning models such as VGG-16, ResNet, Inception, and DenseNet, along with other machine learning approaches and training challenges.",{"name":82,"@type":73,"acceptedAnswer":83},"How is the dataset prepared before training the models?",{"text":84,"@type":76},"The thesis describes preprocessing steps including resizing, normalization, and data augmentation to improve model learning and robustness.","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"]