Computational Psychiatry and Future Perspectives-View Presentation

Video Transcription

Video Summary

The video discussed the concept of computational psychiatry and its promises for the future of psychiatric diagnosis and treatment. It highlighted the use of computational methods such as mathematical modeling, deep learning, and measurement of brain activity to improve the understanding and treatment of psychiatric disorders. The video also presented several presentations on topics such as neuromodulation in psychiatry and brain injury, deep learning for disorder classification, and the use of EEG biomarkers. It emphasized the importance of collaboration and the integration of new technologies, such as internet of things and artificial intelligence, in the field of psychiatry. The speaker discussed the limitations of traditional machine learning approaches and the need for more advanced techniques, such as deep learning. A recent study was presented that used deep learning algorithms to classify major depressive disorder subjects from healthy controls using EEG data. The study found high accuracy in the classification of subjects and highlighted the importance of specific frequency bands in distinguishing between groups. The speaker also emphasized the importance of soft skills and values in education to ensure that humans can differentiate themselves from machines in the future.

Keywords

computational psychiatry

psychiatric diagnosis

psychiatric treatment

mathematical modeling

deep learning

brain activity measurement

neuromodulation

brain injury

disorder classification

EEG biomarkers

internet of things

artificial intelligence