Medical images are playing an increasingly important role in the prevention and diagnosis of diseases. Medical images often contain massive amounts of data. Professional interpretation usually requires a long time of professional study and experience accumulation by doctors. Therefore, the use of super storage and computing power in deep learning as a basis can effectively process a large amount of medical data. Breast cancer brings great harm to female patients, and early diagnosis is the most effective prevention and treatment method, so this project will create a new optimized breast cancer auxiliary diagnosis model based on ResNet. Analyze and process, realize medical aided diagnosis, and provide scientific diagnosis for breast cancer patients.
","abstract_html":"<p>Medical images are playing an increasingly important role in the prevention and diagnosis of diseases. Medical images often contain massive amounts of data. Professional interpretation usually requires a long time of professional study and experience accumulation by doctors. Therefore, the use of super storage and computing power in deep learning as a basis can effectively process a large amount of medical data. Breast cancer brings great harm to female patients, and early diagnosis is the most effective prevention and treatment method, so this project will create a new optimized breast cancer auxiliary diagnosis model based on ResNet. Analyze and process, realize medical aided diagnosis, and provide scientific diagnosis for breast cancer patients.</p>","abstract_has_math":false,"creators":["Li, Yihong"],"institution":null,"degree_name":"Master of Science in Computer Science (MSCS)","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Dr. Mohammed Aledhari","Dr. Chih-Cheng Hung"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-07-14T07:00:00Z","date_published":"2020-07-14T07:00:00Z","updated_at":"2026-07-24T02:43:42Z","subjects":["deep learning","ResNet","Computer Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.kennesaw.edu/cs_etd/34","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Dr. Mohammed Aledhari","Dr. Chih-Cheng Hung"]},{"key":"dc:creator","label":"Author","values":["Li, Yihong"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2021-07-14T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Computer Science (MSCS)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["deep learning","ResNet","Computer Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.kennesaw.edu/cs_etd/34"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Medical images are playing an increasingly important role in the prevention and diagnosis of diseases. Medical images often contain massive amounts of data. Professional interpretation usually requires a long time of professional study and experience accumulation by doctors. Therefore, the use of super storage and computing power in deep learning as a basis can effectively process a large amount of medical data. Breast cancer brings great harm to female patients, and early diagnosis is the most effective prevention and treatment method, so this project will create a new optimized breast cancer auxiliary diagnosis model based on ResNet. Analyze and process, realize medical aided diagnosis, and provide scientific diagnosis for breast cancer patients.
"]},{"key":"dc:title","label":"Title","values":["Deep Learning for Identifying Breast Cancer"]}]}],"canonical_facts":{"dc:contributor":["Dr. Mohammed Aledhari","Dr. Chih-Cheng Hung"],"dc:creator":["Li, Yihong"],"dc:date.available":["2021-07-14T07:00:00Z"],"dc:description.abstract":["Medical images are playing an increasingly important role in the prevention and diagnosis of diseases. Medical images often contain massive amounts of data. Professional interpretation usually requires a long time of professional study and experience accumulation by doctors. Therefore, the use of super storage and computing power in deep learning as a basis can effectively process a large amount of medical data. Breast cancer brings great harm to female patients, and early diagnosis is the most effective prevention and treatment method, so this project will create a new optimized breast cancer auxiliary diagnosis model based on ResNet. Analyze and process, realize medical aided diagnosis, and provide scientific diagnosis for breast cancer patients.
"],"dc:identifier":["https://digitalcommons.kennesaw.edu/cs_etd/34"],"dc:subject":["deep learning","ResNet","Computer Sciences"],"dc:title":["Deep Learning for Identifying Breast Cancer"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Science in Computer Science (MSCS)"]},"updated_at":"2026-07-24T02:43:42Z"}