Neuroscience and Medicine

Volume 9, Issue 4 (December 2018)

ISSN Print: 2158-2912   ISSN Online: 2158-2947

Google-based Impact Factor: 0.67  Citations  

Bipolar and Schizophrenia Disorders Diagnosis Using Artificial Neural Network

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DOI: 10.4236/nm.2018.94021    974 Downloads   2,145 Views  Citations

ABSTRACT

Motivation: Bipolar disorder (BD) and schizophrenia (SZ) has a difficult diagnosis, so the main objective of this article is to propose the use of Artificial Neural Networks (ANNs) to classify (diagnose) groups of patients with BD or SZ from a control group using sociodemographic and biochemical variables. Methods: Artificial neural networks are used as classifying tool. The data from this study were obtained from the array collection from Stanley Neuropathology Consortium databank. Inflammatory markers and characteristics of the sampled population were the inputs variables. Results: Our findings suggest that an artificial neural network could be trained with more than 90% accuracy, aiming the classification and diagnosis of bipolar, schizophrenia and control healthy group. Conclusion: Trained ANNs could be used to improve diagnosis in Schizophrenia and Bipolar disorders.

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Fonseca, M. , Andrades, R. , Bach, S. , Wiener, C. and Oses, J. (2018) Bipolar and Schizophrenia Disorders Diagnosis Using Artificial Neural Network. Neuroscience and Medicine, 9, 209-220. doi: 10.4236/nm.2018.94021.

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