Bipolar and Schizophrenia Disorders Diagnosis Using Artificial Neural Network
| Autor: | Renan Soares de Andrades, Jean Pierre Oses, Carolina David Wiener, Suelen de Lima Bach, Mateus Beck Fonseca |
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| Rok vydání: | 2018 |
| Předmět: |
Schizophrenia disorder
education.field_of_study Artificial neural network business.industry Schizophrenia (object-oriented programming) Population Neuropathology medicine.disease 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine mental disorders Medicine Bipolar disorder business education Neuroscience 030217 neurology & neurosurgery |
| Zdroj: | Neuroscience and Medicine. :209-220 |
| ISSN: | 2158-2947 2158-2912 |
| DOI: | 10.4236/nm.2018.94021 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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