Intelligent clinical decision support systems for non-invasive bladder cancer diagnosis

  • Authors:
  • Alexandru G. Floares;Carmen loares;Oana Vermesan;Tiberiu Popa;Michael Williams;Sulaimon Ajibode;Liu Chang-Gong;Diao Lixia;Wang Jing;Traila Nicola;David Jackson;Colin Dinney;Liana Adam

  • Affiliations:
  • OncoPredict & SAIA & IOCN, Artificial Intelligence Department, Cluj-Napoca, Romania;OncoPredict & IOCN, Department of Medical Oncology, Cancer Institute, Cluj - Napoca, Romania;OncoPredict & SAIA & IOCN, Artificial Intelligence Department, Cluj-Napoca, Romania;OncoPredict & SAIA & IOCN, Artificial Intelligence Department, Cluj-Napoca, Romania;UT-MD Anderson Cancer Center, Departments of Urology and Bioinformatics, Houston, Tx;UT-MD Anderson Cancer Center, Departments of Urology and Bioinformatics, Houston, Tx;UT-MD Anderson Cancer Center, Departments of Urology and Bioinformatics, Houston, Tx;UT-MD Anderson Cancer Center, Departments of Urology and Bioinformatics, Houston, Tx;UT-MD Anderson Cancer Center, Departments of Urology and Bioinformatics, Houston, Tx;UMF, Timisoara, Romania;Life Biosystems, Heidelberg, Germany;UT-MD Anderson Cancer Center, Departments of Urology and Bioinformatics, Houston, Tx;UT-MD Anderson Cancer Center, Departments of Urology and Bioinformatics, Houston, Tx

  • Venue:
  • CIBB'10 Proceedings of the 7th international conference on Computational intelligence methods for bioinformatics and biostatistics
  • Year:
  • 2010

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Abstract

The aim of this study was to find the set of biomarkers based on plasma microRNAs which can predict in a noninvasive way the diagnosis of bladder cancer. We presented here a methodology and the related concepts to develop intelligent molecular biomarkers using knowledge discovery in data and artificial intelligence methods. To the best of our knowledge, this is the first time when plasma miRNAs are combined using artificial intelligence and the prediction accuracy of the developed systems for medical decision support is the best published by now, some of them having even 100%.