/ML-Breast-Cancer-Classification

Technicians can use a microscope to observe tissue samples that were taken from patients who are suspected to have breast cancer. By looking at the size and shape of the nuclei present within these tissue samples, one can then predict whether a given sample appears to be cancerous. In this document I demonstrate an automated methodology to predict if a sample is benign or malignant given measurements of nuclear shape that were made from digital images of fine needle aspirates of breast tissue masses from clinical samples.

Primary LanguageJupyter Notebook

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