On Mistakes We Made in Prior Computational Psychiatry Data Driven Approach Projects and How They Jeopardize Translation of Those Findings in Clinical Practice
| Autor: | Milena Čukić, Dragoljub Pokrajac, Viktoria Lopez |
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| Rok vydání: | 2020 |
| Předmět: |
0303 health sciences
medicine.medical_specialty Computer science Process (engineering) media_common.quotation_subject 3. Good health Data-driven Task (project management) Clinical Practice 03 medical and health sciences 0302 clinical medicine Optimism medicine Psychiatry 030217 neurology & neurosurgery 030304 developmental biology media_common |
| Zdroj: | Advances in Intelligent Systems and Computing ISBN: 9783030551896 IntelliSys (3) |
| DOI: | 10.1007/978-3-030-55190-2_37 |
| Popis: | In this work, we aimed at comparing our findings in depression detection task with similar methodologies applied in present literature. In our project we showed that when electrophysiological signal (in this case electroencephalogram, EEG) is characterized by nonlinear measures, any of seven most popular classifiers yields high accuracy on the task. Following every step done in this process we elaborated on other findings mainly from analysis of electrical signals or nonlinear analysis showing what would be optimal for further research. We focused on discussing various possible mistakes and differences that could potentially lead to unwarranted optimism and other misinterpretations of results. We also consider obstacles that this practice would be accepted for real-life application in psychiatry and some ideas how to overcome them. In Conclusion we summarize recommendation for future research in order to be easily applicable in clinical practice. |
| Databáze: | OpenAIRE |
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