Artificial Intelligence Clinical Trial
Official title:
Correlation of Audiovisual Features With Clinical Variables and Neurocognitive Functions in Bipolar Disorder, Mania
The aim of this study is to show the physiological changes during manic episode in bipolar mania how much they differentiate from remission and healthy control. Relation of audio-visual features as physiological changes and cognitive functions and clinical variables will be searched. The aim is to find biologic markers for predictors of treatment response via machine learning techniques to be able to reduce treatment resistance and give an idea for personalized treatment of bipolar patients.
The objective of this research protocol is to find audio-visual features which differentiates bipolar mani/ remission/ health/ simulation and predicts treatment response earlier and detect neurocognitive changes during mania/ remission and difference from the healthy control. During hospitalization in every follow up day (0th- 3rd- 7th- 14th- 28th day) and after discharge on the 3rd month, presence of depressive and manic features for patients was evaluated using Young Mania Rating Scale(YMRS) and Montgamery- Asberg Depresyon Scale (MADRS). Audiovisual recording is done by a video camera in every follow up day for patients and for healthy controls which includes also depression and mania simulation. Cambridge Neurophysiological Assessment Battery (CANTAB) were administered to both groups( for patients both in the manic phase and in the remission) to assess neurocognitive functions. ;
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