Ontology highlight
ABSTRACT:
SUBMITTER: Dhahri H
PROVIDER: S-EPMC7064857 | biostudies-literature | 2020
REPOSITORIES: biostudies-literature
BioMed research international 20200227
Breast cancer is the most diagnosed cancer among women around the world. The development of computer-aided diagnosis tools is essential to help pathologists to accurately interpret and discriminate between malignant and benign tumors. This paper proposes the development of an automated proliferative breast lesion diagnosis based on machine-learning algorithms. We used Tabu search to select the most significant features. The evaluation of the feature is based on the dependency degree of each attr ...[more]