Bipolar and Schizophrenia Disorders Diagnosis Using Artificial Neural Network

• 作者: Carolina David Wiener Jean Pierre Oses Mateus Beck Fonseca Renan Soares de Andrades Suelen de Lima Bach
• 来源期刊: 神经系统科学与医药(英文)
• 学科: 医学
• 关键词: BIPOLAR DISORDER SCHIZOPHRENIA DISORDER Biomarkers Artificial NEURAL Network
• 年，卷（期）: 2018,（4）
• 页码范围: 209-220
• 页数: 12页
• 分类号: R73

摘要

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.