چکیده مقاله
Since breast cancer is the second most common cause of death for women, timely, precise identification can lower the mortality rate With the use of computers, radiologists may quickly find problems Information on the detection and diagnosis of numerous diseases and anomalies may be found in medical photographs Radiologists may examine the interior structure using a variety of modalities, and many forms of research have shown a lot of interest in these modalities Each of these modalities is extremely important in various medical sectors This article seeks to give a review that highlights recent advances in the detection and classification of breast cancer using machine learning and deep learning technology It initially offers a summary of the various machine learning methodologies, followed by a summary of the different deep learning techniques and particular architectures for detecting and classifying breast cancer To offer a thorough introduction to the field This study concludes by summarizing the upcoming developments and difficulties in identifying and categorizing breast cancer
کلیدواژهها
نویسندگان
Mona Naseredin
۱ Department of Information Technology Group, Barajin University, Qazvin, Iran
Farzane Tajidini
۲ Tabarestan University of Chalus, Chalus, Iran
Saeed Khodadadi-fard
۳ Department of Community Medicine, Faculty of Medicine, Ardabil University of Medical Science, Ardabil, Iran
شیوه ارجاع
Naseredin، Mona و Tajidini، Farzane و Khodadadi-fard، Saeed،1401،A review of Deep learning in breast cancer،نهمین کنگره ملی تازه های مهندسی برق و کامپیوتر ایران،تهران
ارائهشده در
یازدهمین کنگره ملی مهندسی برق و کامپیوتر ایران با تاکید بر فن آوری های بومی ایران20 بهمن 1405 تا 21 بهمن 1405 · تهران