Mining balance disorders' data for the development of diagnostic decision support systems.
In this work we present the methodology for the development of the EMBalance diagnostic Decision Support System (DSS) for balance disorders. Medical data from patients with balance disorders have been analysed using data mining techniques for the development of the diagnostic DSS. The proposed methodology uses various data, ranging from demographic characteristics to clinical examination, auditory and vestibular tests, in order to provide an accurate diagnosis. The system aims to provide decision support for general practitioners (GPs) and experts in the diagnosis of balance disorders as well as to provide recommendations for the appropriate information and data to be requested at each step of the diagnostic process. Detailed results are provided for the diagnosis of 12 balance disorders, both for GPs and experts. Overall, the reported accuracy ranges from 59.3 to 89.8% for GPs and from 74.3 to 92.1% for experts.
Institute of Communication and Computer Systems, National Technical University of Athens, Athens, Greece.
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Exarchos
Unit of Medical Technology and Intelligent Information Systems, Dept. of Materials Science and Engineering, University of Ioannina, Ioannina, Greece.
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Rigas
1st Otolaryngology Department, National and Kapodistrian University of Athens, Athens, Greece.
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Bibas
1st Otolaryngology Department, National and Kapodistrian University of Athens, Athens, Greece.
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Kikidis
1st Otolaryngology Department, National and Kapodistrian University of Athens, Athens, Greece.
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Nikitas
Antwerp University Research centre for Equilibrium and Aerospace, Antwerp, Belgium.
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Wuyts
Antwerp University Research centre for Equilibrium and Aerospace, Antwerp, Belgium.
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Ihtijarevic
Ghent University, Ghent, Belgium.
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Maes
University Medical Center Freiburg, Freiburg, Germany.
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Cenciarini
University Medical Center Freiburg, Freiburg, Germany.
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Maurer
University College London Ear Institute, London, UK.
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Macdonald
City University, London, UK.
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Bamiou
City University, London, UK.
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Luxon
Institute of Communication and Computer Systems, National Technical University of Athens, Athens, Greece; Unit of Medical Technology and Intelligent Information Systems, Dept. of Materials Science and Engineering, University of Ioannina, Ioannina, Greece; 1st Otolaryngology Department, National and Kapodistrian University of Athens, Athens, Greece; Antwerp University Research centre for Equilibrium and Aerospace, Antwerp, Belgium; Ghent University, Ghent, Belgium; University Medical Center Freiburg, Freiburg, Germany; University College London Ear Institute, London, UK; City University, London, UK.
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Prasinos
City University, London, UK.
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Spanoudakis
Institute of Communication and Computer Systems, National Technical University of Athens, Athens, Greece.
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Koutsouris
Unit of Medical Technology and Intelligent Information Systems, Dept. of Materials Science and Engineering, University of Ioannina, Ioannina, Greece. Electronic address: fotiadis@cc.uoi.gr.
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Fotiadis
D000465:Algorithms; D057225:Data Mining / Q000379:methods*; D020000:Decision Support Systems, Clinical; D003661:Decision Support Techniques; D003663:Decision Trees; D006801:Humans; D004856:Postural Balance / Q000502:physiology; D014717:Vertigo / Q000175:diagnosis; D014722:Vestibule, Labyrinth / Q000502:physiology*
Balance disorders; Data mining; Decision support systems; Vestibular system