Clinical decision support system for decision making in mammary glands thermography

Authors

  • M. B. Bastida Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
  • M. E. Cabello Universidad de Colima, Campus Colima, Colima, México
  • A. L. Rodríguez Universidad Nacional Autónoma de México, Campus Juriquilla, Querétaro, México
  • J. García UNEME-DEDICAM, Querétaro, México

DOI:

https://doi.org/10.17488/RMIB.38.1.12

Keywords:

Clinical decision support systems (CDSS), decision trees, weight factor, breast cancer, thermography

Abstract

A decision tree based system with heuristic weight factors oriented to diagnosis by thermography was developed. The proposed clinical decision support system (CDSS) includes binary decision trees for statistical classification of some diseases of the mammary gland. These include weight constant factors found by the correlation of the variables involved in the development of breast disorders according to the statistical attachment of the thermal features, as well as complementary clinical information (medical history, physical parameters, genetic load and habits, among others), regarding its diagnostic incidence. The certainty of the system for inflammatory disorders is 96%, for fibrocystic mastopathy is 78 %, for fat necrosis is 62% and for breast cancer is 86%. The 14% error is associated to microcalcifications that with the reported thermographic technique it is not possible to differentiate. Thus, it is possible to catalog the risk of a patient having a condition according to the results obtained after conducting a thermal test. Then, with the CDSS the possibility of applying early detection tests in the population suffering from contraindications to perform the others is improved, in addition it allows a comprehensive diagnosis for other patients.

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Published

2017-01-15

How to Cite

Bastida, M. B., Cabello, M. E., Rodríguez, A. L., & García, J. (2017). Clinical decision support system for decision making in mammary glands thermography. Revista Mexicana De Ingenieria Biomedica, 38(1), 166–187. https://doi.org/10.17488/RMIB.38.1.12

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