Use of TensorFlow and neural networks
Diagnosis-
Malignant (Tumor that must be removed) Benign (Tumor that is not cancerous)
{ 1= malignant } { 0= benign }
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This is considered supervised machine learning because we know for a fact that the tumor is malignant or benign (given data)
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measurements describe properties of the cell's nucleus (eg, perimetr, texture, area, size)
From Wisconson's breast cancer dataset which is a simplified clean version of the dataset here: https://www.kaggle.com/uciml/breast-cancer-wisconsin-data)
Install dependencies: pip3 install pandas sklearn tensorflow keras
Research-
https://www.kaggle.com/amandam1/breastcancerdataset https://www.jmir.org/2019/7/e14464/ https://bmcresnotes.biomedcentral.com/articles/10.1186/s13104-019-4121-7 https://data.gov.uk/ https://www.kaggle.com/raghadalharbi/breast-cancer-gene-expression-profiles-metabric https://www.tensorflow.org/api_docs/python/tf/all_symbols
*Not actual application that can be used