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Application of Artificial Neural Networks to Identify Alzheimer’s Disease Using Cerebral Perfusion SPECT Data

Author

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  • Dariusz Świetlik

    (Intrafaculty College of Medical Informatics and Biostatistics, Medical University of Gdańsk, 1 Debinki St., 80-211 Gdańsk, Poland)

  • Jacek Białowąs

    (Department of Anatomy and Neurobiology, Medical University of Gdańsk, 1 Debinki St., 80-211 Gdańsk, Poland)

Abstract

The aim of this study was to demonstrate the usefulness of artificial neural networks in Alzheimer disease diagnosis (AD) using data of brain single photon emission computed tomography (SPECT). The results were compared with discriminant analysis. The study population consisted of 132 clinically diagnosed patients. There were 72 subjects with AD and 60 belonging to the normal control group. The artificial neural network used 36 numerical values being the count numbers obtained for each area of brain SPECT. These numbers determined the set of input data for the artificial neural network. The sensitivity of Alzheimer disease diagnosis detection by artificial neural network and discriminant analysis were 93.8% and 86.1%, respectively, and the corresponding specificity was 100% and 95%. We also used receiver operating characteristic curve (ROC) analysis and areas under receiver operating characteristics curves were correspondingly 0.97 ( p < 0.0001) for the artificial neural networks (ANN) and 0.96 ( p < 0.0001) for discriminant analysis. In conclusion, artificial neural networks and conventional statistics methods (discriminant analysis) are a useful tool in Alzheimer disease diagnosis.

Suggested Citation

  • Dariusz Świetlik & Jacek Białowąs, 2019. "Application of Artificial Neural Networks to Identify Alzheimer’s Disease Using Cerebral Perfusion SPECT Data," IJERPH, MDPI, vol. 16(7), pages 1-9, April.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:7:p:1303-:d:221946
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    References listed on IDEAS

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    1. Dariusz Świetlik, 2018. "Simulations of Learning, Memory, and Forgetting Processes with Model of CA1 Region of the Hippocampus," Complexity, Hindawi, vol. 2018, pages 1-13, December.
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    Cited by:

    1. Agata Ossowska & Aida Kusiak & Dariusz Świetlik, 2022. "Artificial Intelligence in Dentistry—Narrative Review," IJERPH, MDPI, vol. 19(6), pages 1-10, March.
    2. Dariusz Świetlik & Aida Kusiak & Agata Ossowska, 2022. "Computational Modeling of Therapy with the NMDA Antagonist in Neurodegenerative Disease: Information Theory in the Mechanism of Action of Memantine," IJERPH, MDPI, vol. 19(8), pages 1-12, April.

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