A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
Prediction of breast cancer risk using a machine learning approach embedded with a locality preserving projection algorithm
2018
Physics in Medicine and Biology
In order to automatically identify a set of effective mammographic image features and build an optimal breast cancer risk stratification model, this study aims to investigate advantages of applying a machine learning approach embedded with a locally preserving projection (LPP) based feature combination and regeneration algorithm to predict short-term breast cancer risk. A dataset involving negative mammograms acquired from 500 women was assembled. This dataset was divided into two age-matched
doi:10.1088/1361-6560/aaa1ca
pmid:29239858
pmcid:PMC5801007
fatcat:fnocoi634zgpxaeea3rbxyq5qy