Imperial College London
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Professor Maria Kyrgiou

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

Chair in Gynaecologic Oncology
 
 
 
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Contact

 

+44 (0)20 7594 2177m.kyrgiou Website

 
 
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Location

 

Institute of Reproductive and Developmental BiologyHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@article{Salamalekis:2019:10.4018/IJRQEH.2019040102,
author = {Salamalekis, E and Pouliakis, A and Margari, N and Kottaridi, C and Spathis, A and Karakitsou, E and Gouloumi, AR and Leventakou, D and Chrelias, G and Valasoulis, G and Nasioutziki, M and Kyrgiou, M and Dinas, K and Panayiotides, IG and Paraskevaidis, E and Chrelias, C},
doi = {10.4018/IJRQEH.2019040102},
journal = {International Journal of Reliable and Quality E-Healthcare},
pages = {15--35},
title = {An Artificial Intelligence Approach for the Detection of Cervical Abnormalities: Application of the Self Organizing Map},
url = {http://dx.doi.org/10.4018/IJRQEH.2019040102},
volume = {8},
year = {2019}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Numerous ancillary techniques detecting HPV DNA or mRNA are viewed as competitors or ancillary techniques to test Papanicolaou. However, no technique is perfect because sensitivity increases at the cost of specificity. Various methods have been applied to resolve this issue by using many examination results, such as classification and regression trees and supervised artificial neural networks. In this article, 1258 cases with results from test Pap, HPV DNA, HPV mRNA, and p16 were used to evaluate the performance of the self-organizing map (SOM). An artificial neural network has three advantages: it is unsupervised, can tolerate missing data, and produces topographical maps. The results of the SOM application were encouraging and produced maps depicting the important tests.
AU  - Salamalekis,E
AU  - Pouliakis,A
AU  - Margari,N
AU  - Kottaridi,C
AU  - Spathis,A
AU  - Karakitsou,E
AU  - Gouloumi,AR
AU  - Leventakou,D
AU  - Chrelias,G
AU  - Valasoulis,G
AU  - Nasioutziki,M
AU  - Kyrgiou,M
AU  - Dinas,K
AU  - Panayiotides,IG
AU  - Paraskevaidis,E
AU  - Chrelias,C
DO  - 10.4018/IJRQEH.2019040102
EP  - 35
PY  - 2019///
SN  - 2160-9551
SP  - 15
TI  - An Artificial Intelligence Approach for the Detection of Cervical Abnormalities: Application of the Self Organizing Map
T2  - International Journal of Reliable and Quality E-Healthcare
UR  - http://dx.doi.org/10.4018/IJRQEH.2019040102
VL  - 8
ER  -
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