About this Research Topic
Mental health is affected by various factors, including neurotransmitter changes, genetic factors, environmental factors, neurodevelopmental factors, and autoimmune and inflammatory diseases. The current diagnosis of mental disorders is still based on the patient's clinical disease history, observed behaviors, subjective reports, and results of the mental state examination. Neuroimaging and diagnostic tests include electroencephalography, genotype, toxicology, and serology. Based on the above multi-source data and multi-modal analysis, various calculation methods play an essential role in the judgment of mental health and provide a solution further to explore the pathogenesis of psychiatric disorders and mental health.
This research topic aims to explore mental abnormalities and their pathogenesis through the computational method. Multiple factors accompany mental abnormalities and disorders and involve multiple aspects. With the development of high measurement and information technology, massive biomedical data has been brought, including literature, sequencing data, genome data, and various medical image data. These multi-source and multi-modal data carry rich knowledge. Mining and analyzing the application of computing means will further deepen the understanding of the pathogenesis of psychosis.
Topics of interest include, but are not limited to following fields:
1. Data and text mining for mental health and psychiatric disorders;
2. Statistical computing models based on mental health;
3. Computational models for autism and other mental disorders;
4. Knowledge graph related to mental health;
5. Research on psychological health and psychiatric disorders based on deep learning;
6. Multi-modal research on mental and psychiatric disorders;
7. Knowledge integration of multi-source mental and psychiatric disorders;
8. Construction of graph of multi-source autism and other mental diseases;
9. Research on mental disorder mechanisms based on single-cell technology.
This research topic aims to explore mental abnormalities and their pathogenesis through the computational method. Multiple factors accompany mental abnormalities and disorders and involve multiple aspects. With the development of high measurement and information technology, massive biomedical data has been brought, including literature, sequencing data, genome data, and various medical image data. These multi-source and multi-modal data carry rich knowledge. Mining and analyzing the application of computing means will further deepen the understanding of the pathogenesis of psychosis.
Topics of interest include, but are not limited to following fields:
1. Data and text mining for mental health and psychiatric disorders;
2. Statistical computing models based on mental health;
3. Computational models for autism and other mental disorders;
4. Knowledge graph related to mental health;
5. Research on psychological health and psychiatric disorders based on deep learning;
6. Multi-modal research on mental and psychiatric disorders;
7. Knowledge integration of multi-source mental and psychiatric disorders;
8. Construction of graph of multi-source autism and other mental diseases;
9. Research on mental disorder mechanisms based on single-cell technology.
Keywords: Mental Health, Neurotransmitter Changes, Genetic Factors, Multi-source Data, Multi-modal Analysis, Data Mining
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