Literature DB >> 18260271

[Artificial neural networks for decision making in urologic oncology].

M Remzi1, B Djavan.   

Abstract

This chapter presents a detailed introduction regarding Artificial Neural Networks (ANNs) and their contribution to modern Urologic Oncology. It includes a description of ANNs methodology and points out the differences between Artifical Intelligence and traditional statistic models in terms of usefulness for patients and clinicians, and its advantages over current statistical analysis.

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Year:  2007        PMID: 18260271     DOI: 10.1016/j.anuro.2007.04.003

Source DB:  PubMed          Journal:  Ann Urol (Paris)        ISSN: 0003-4401


  1 in total

1.  Effective diagnosis of coronary artery disease using the rotation forest ensemble method.

Authors:  Esra Mahsereci Karabulut; Turgay Ibrikçi
Journal:  J Med Syst       Date:  2011-09-13       Impact factor: 4.460

  1 in total

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