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Publikováno v:
IEEE Access, Vol 12, Pp 93993-94007 (2024)
Breast cancer is a major health problem worldwide, and an accurate prediction of its recurrence is crucial to early detection of recurrence and personalized treatment. In recent years, various AI techniques have been applied to predict cancer recurre
Externí odkaz:
https://doaj.org/article/8e14ef14b03143eb88d995f837ffef7d
Autor:
Salini Sasidharan Nair, Mohan Subaji
Publikováno v:
IEEE Access, Vol 12, Pp 87560-87578 (2024)
Breast cancer, a global health concern, requires innovative diagnostic approaches. The potential of Artificial Intelligence and Machine Learning in breast cancer diagnosis warrants exploration along with conventional methods. Our method partitions br
Externí odkaz:
https://doaj.org/article/30d7f55b0e6845cd847a08ec1ebacbc9
Autor:
MD Shakhawat Hossain, MD. Sahilur Rahman, Munim Ahmed, Nazia Alfaz, Sirajum Munira Shifat, M. M. Mahbubul Syeed, Mohammad Anowar Hussen, Mohammad Faisal Uddin
Publikováno v:
IEEE Access, Vol 12, Pp 86083-86095 (2024)
Residual tumor cellularity (RTC) is assessed routinely after neoadjuvant therapy (NAT) for Breast Cancer (BC) patients to determine the effectiveness of therapy and plan the treatment. RTC is also considered a prognostic biomarker associated with met
Externí odkaz:
https://doaj.org/article/a6459dbf29f94d92a909df7c62d049fb
Publikováno v:
IEEE Access, Vol 12, Pp 72794-72812 (2024)
The field of healthcare analytics, as an expanding discipline that integrates data analysis, machine learning, and clinical expertise, is seen to hold great promise for improving patient outcomes and the overall delivery of healthcare services. With
Externí odkaz:
https://doaj.org/article/4f36aba6634048e38cf4d9d49ace4a72
Autor:
Ruiming Zeng, Boan Qu, Wei Liu, Jianghao Li, Hongshen Li, Pingping Bing, Shuangni Duan, Lemei Zhu
Publikováno v:
IEEE Access, Vol 12, Pp 70825-70832 (2024)
Breast cancer is a type of disease that primarily affects the breast tissue, and it is crucial to achieve early diagnosis for successful treatment and recovery. In recent years, the residual network (ResNet) has gained significant attention in the de
Externí odkaz:
https://doaj.org/article/9ce9961a8cfb49e0b70b78c7020154c4
Publikováno v:
IEEE Access, Vol 12, Pp 67889-67909 (2024)
Artificial intelligence algorithms, specifically deep learning, can assist radiologists by automating mammogram density assessment. However, trust in such algorithms must be established before they are widely adopted in clinical settings. In this stu
Externí odkaz:
https://doaj.org/article/f3d517d529d24d589caae799c30676ee
Publikováno v:
IEEE Access, Vol 12, Pp 68697-68710 (2024)
Breast cancer is the most commonly diagnosed cancer among women, globally. The occurrence and fatality rates are high for breast cancer compared to other types of cancer. The World Cancer report 2020 points out early detection and rapid treatment as
Externí odkaz:
https://doaj.org/article/13d4e5790d1d4caf9a1b1c308096fdc4
Autor:
Soumya Sara Koshy, L. Jani Anbarasi
Publikováno v:
IEEE Access, Vol 12, Pp 52051-52066 (2024)
Breast cancer is a deadly disease commonly affecting women. One method to avoid death from breast cancer is to obtain a diagnosis early. Breast cancer detection is a significant area that benefits from the technological advancements in artificial int
Externí odkaz:
https://doaj.org/article/432b621337554a528ab70872d6f496c5
Publikováno v:
IEEE Access, Vol 12, Pp 50431-50443 (2024)
There are millions of cancer cases worldwide every year, and breast cancer is one of the most prevalent diseases with the highest mortality rate. The manual effort of pathologists can be significantly reduced by computerized diagnostic systems, which
Externí odkaz:
https://doaj.org/article/5fbcd5f7784f49d9926314c257ae0eb3
Publikováno v:
IEEE Access, Vol 12, Pp 46093-46103 (2024)
The Human Epidermal Growth Factor Receptor 2 (HER2) is one of the aggressive subtypes of breast cancer. The HER2 status decides the requirement of breast cancer patients to receive HER2-targeted therapy. The HER2 testing involves combining Immunohist
Externí odkaz:
https://doaj.org/article/1cac43b5fd50458a946b5c8c85628062