What is it about?
Novel computational methods have been developed to assist cervical cancer diagnosis, but the relationship between the digital information of the colposcopy test and histopathology data has not been completely studied. This paper shows the comparison of three well-known computational methods to try to discriminate among different kind of tissues to improve colposcopy test considering histopathologic data.
Featured Image
Photo by Omar Lopez on Unsplash
Why is it important?
Our findings show there is a relation between computational representation of a reaction that happens during colposcopy and histopathologic data, this information can be used when physicians do not have a histopathological laboratory or they need to obtain a representative biopsy guided by colposcopy based on a computational representation.
Perspectives
Writing this article was an important opportunity to note that the study of the relationship of the colposcopy and histopathology tests from the computational point of view will allow the improvement of the diagnostic methods that are available until now.
Karina Gutiérrez Fragoso
Instituto Tecnológico Superior del Oriente del Estado de Hidalgo
Read the Original
This page is a summary of: Optimization of Classification Strategies of Acetowhite Temporal Patterns towards Improving Diagnostic Performance of Colposcopy, Computational and Mathematical Methods in Medicine, January 2017, Hindawi Publishing Corporation,
DOI: 10.1155/2017/5989105.
You can read the full text:
Contributors
The following have contributed to this page
