Computational method to diagnose breast cancer
2017
Northwest University, Xi’an, China
The study describes the development of a computational method to detect clustered microcalcifications from mammograms for early diagnosis of breast cancer. Based on a series of algorithms, this method allows classifying the samples in lesioned or normal breast tissues. When tested with synthetic and real samples, it reduces false-positive rates while maintaining the true positive rate. This computational tool can potentially be useful for the early diagnosis of breast cancer.
Grouped fuzzy SVM with EM-based partition of sample space for clustered microcalcification detection
Jun Feng
Added on: 08-01-2021
[1] https://content.iospress.com/articles/technology-and-health-care/thc1336[2] https://data.jrc.ec.europa.eu/dataset/ffebe454-ed9a-47cf-8a33-8cf70c1b7d38
