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- W4386804945 abstract "The most common malignancy among women is breast cancer. The identification of the breast cancer in primary stage of its formation is highly desirable as the mortality rate of such cancers is always a concern for the society. However, there exists many such solutions that prove their applicability in the cure of the cancer types but all such methods are on clinical aspects. In addition, research was conducted on Computer Aided Diagnosis (CAD) systems that can assist in cancer prediction utilizing AI-based approaches. Such an intelligent systems can help the radiologists to make the better predictions based on the generated reports using CAD systems. These systems are always considered a beneficial tool to the radiologists to get faster, more precise and approximate results about abnormalities and thus considered as a second opinion aspect for them. This paper presents the detailed systematic study about all such works that uses the CAD systems incorporated with the fast AI and machine learning algorithms for making decisions on tasks of classification of cancer cells using the histology imaging and segmentation of the abnormality regions from the input histology images. The collective study, as presented in this work, help in understanding the latest works on the above said domain with the summarized results on the approaches used, dataset types, and their performance metrics. Thus the objective of work to summarize the overall result on histology imaging is fulfilled in this article." @default.
- W4386804945 created "2023-09-17" @default.
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- W4386804945 date "2023-01-01" @default.
- W4386804945 modified "2023-09-27" @default.
- W4386804945 title "A Systematic Study of Breast Cancer Detection by Using Algorithms of Machine Intelligence" @default.
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- W4386804945 doi "https://doi.org/10.1007/978-981-99-3716-5_32" @default.
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