Methodology for the application of data science in breast cancer diagnosis

Abstract

In 2020 the detected cases of breast cancer in Colombia were 15,509 of which 4,411 ended in death. The anticipate prognosis of this disease has become a research need because it can facilitate preventive treatment to avoid its lethality in an advanced stage. This paper proposes the DSM-BCD methodology (Data science methodology for breast cancer diagnosis) designed to speed up the diagnosis of breast cancer through the continuous improvement of Machine Learning and Deep Learning techniques based on the insight of the oncology specialist and the feedback of knowledge according to the behavior of the data in the various techniques for the detection of breast cancer.

Keywords

• Breast Cancer
• Data Science
• Diagnostics
• Machine Learning
• Methodology

References

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