Psycho Web: A Machine Learning Platform for the Diagnosis and Classification of Mental Disorders
In this paper, we present the development of a platform to collect data from cases diagnosed with mental disorders. It includes the use of a Machine Learning classification algorithm, k-NN with TF-IDF, to automatically identify the type of mental disorder suffered by a patient given his/her symptoms, when evaluated by a mental health professional. The platform called “Psycho Web” has a friendly web interface that will allow ergonomic interaction between the mental health professional and the system. The dataset used for the initial evaluation of our platform is composed of 114 instances in total, 56% of which were obtained from the taxonomy proposed by ICD-10. The rest of the instances correspond to real cases, whose symptoms and diagnoses were taken by professionals who voluntarily collaborated with the project. A raw application of the algorithm to the data available shows results with errors that go down to 5%.
KeywordsMachine learning Diagnosis prediction Mental disorders ICD-10 k-NN TF-IDF
This work was supported by IDEIAGEOCA Research Group of Universidad Politécnica Salesiana in Quito, Ecuador.
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