Computational Approaches in Psychiatry and Neuropsychiatry: Issues and Challenges on Mental Disorders
A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Digital Health".
Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 4502
Special Issue Editors
Interests: automated deception detection; sentiment analysis; computational psychiatry
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Reduced availability of psychiatrists and therapists, the increasing supply of computational resources, and the ease of large-scale data processing have amplified the value of computing-based methods, allowing at least partial automation of some activities related to the diagnosis and treatment of mental disorders.
This Special Issue is devoted to computer methods of assisting researchers and clinicians in the fields of psychology, psychiatry and neuropsychiatry. We are seeking articles that address screening, clinical diagnosis, and therapy, using all kinds of computational methods. Deep learning and machine learning are of particular interest, but submissions from broadly understood computational data analysis are also welcome.
Potential topics include (but are not limited to):
- Methods supporting clinical diagnosis and treatment using computer-based approaches.
- Using computational data analysis to identify disorder-related signals at various stages.
- Detecting phenomena such as prosody, emotions, sentiment, metaphors, and various semantic, syntactic, and behavioral patterns in relation to mental disorders and psychiatric conditions.
- Automated disorder detection from one modality data (e.g., text, sound, and video).
- Automated disorder detection from multimodal data.
- Hybrid methods, data fusion, and the design of effective multimodal feature spaces and vector representations.
- Using social media data to detect potential disorders from online samples to support large-scale automated screening.
- Deep learning applied to neuroimaging data (e.g., MRI, EEG) to diagnose disorders.
- Computer support for therapy and treatment, including avatars and therapy bots using both text and multimodal interfaces.
- Issues of dialogue systems and natural language generation.
Dr. Aleksander Wawer
Dr. Izabela Stefaniak
Guest Editors
Manuscript Submission Information
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Keywords
- computational psychiatry
- disorder detection using machine learning
- automating diagnosis
- computer-aided therapy
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