Artificial intelligence (AI) has made an indelible contribution to the progress and development of human society, which has major applications in the fields of national defense, transportation, finance, logistics, education, etc. As a branch of computer science, AI has made significant breakthroughs in machine translation, intelligent control, language and image processing, automatic programming, and storage computing. Therefore, there is reason to believe that AI can make greater contributions to the prevention and diagnosis of mental disorders.
There have been relevant representative studies based on AI technology that have made breakthrough contributions in the prevention, diagnosis, and treatment of other diseases. For example, deep learning algorithms are used to analyze medical images to diagnose diseases; AI-based expert systems are used to replace human experts to diagnose and treat diseases; disease diagnosis based on medical big data; cloud computing based on neural networks is used to combat COVID-19 and so on. However, at present, there is still a lack of research on the prevention or diagnosis of mental disorders using AI-related technologies.
In order to improve the applicability of AI technology in the mental disorder field, it is necessary to propose new theories, technologies, architectures, algorithms, and mechanisms. The goal of this Research Topic is to bring together relevant researchers from industry and academia to share their latest findings and developments in the application of AI in medicine, especially in the prevention and diagnosis of mental disorders. We aim to look for contributions that try to integrate machine learning and AI techniques into the designing of algorithms for smart mental health care systems. We welcome submissions of high-quality original research and review in this field. Topics of interest include, but are not limited to:
1. The technology, modeling, and mechanism of AI in mental disorders prevention/diagnosis/treatment applications.
2. Application and modeling of human affective computing in the diagnosis of mental disorders.
3. Intelligent human-computer interaction medical systems based on natural language processing, especially system modeling in the field of psychiatry.
4. The application of human posture recognition in the diagnosis of mental disorders.
5. The application of smart medical treatment in the smart mental health care system.
6. Development of a real-time patient monitoring system based on AI.
7. Application of blockchain/Internet of Things (IoT)/cloud computing/big data in the field of psychiatric medicine.
8. Construction of the medical experimental platform based on AI, especially in the field of psychiatric medicine.
9. Secure and reliable IoT, edge, and cloud services for digital healthcare.
10. Methods for processing healthcare data in edge and cloud.
11. Computation, data, and network management to facilitate IoT, edge, and cloud integration in the domain of healthcare.
12. The application of AI to mobile passive data analyses for mental health.
Artificial intelligence (AI) has made an indelible contribution to the progress and development of human society, which has major applications in the fields of national defense, transportation, finance, logistics, education, etc. As a branch of computer science, AI has made significant breakthroughs in machine translation, intelligent control, language and image processing, automatic programming, and storage computing. Therefore, there is reason to believe that AI can make greater contributions to the prevention and diagnosis of mental disorders.
There have been relevant representative studies based on AI technology that have made breakthrough contributions in the prevention, diagnosis, and treatment of other diseases. For example, deep learning algorithms are used to analyze medical images to diagnose diseases; AI-based expert systems are used to replace human experts to diagnose and treat diseases; disease diagnosis based on medical big data; cloud computing based on neural networks is used to combat COVID-19 and so on. However, at present, there is still a lack of research on the prevention or diagnosis of mental disorders using AI-related technologies.
In order to improve the applicability of AI technology in the mental disorder field, it is necessary to propose new theories, technologies, architectures, algorithms, and mechanisms. The goal of this Research Topic is to bring together relevant researchers from industry and academia to share their latest findings and developments in the application of AI in medicine, especially in the prevention and diagnosis of mental disorders. We aim to look for contributions that try to integrate machine learning and AI techniques into the designing of algorithms for smart mental health care systems. We welcome submissions of high-quality original research and review in this field. Topics of interest include, but are not limited to:
1. The technology, modeling, and mechanism of AI in mental disorders prevention/diagnosis/treatment applications.
2. Application and modeling of human affective computing in the diagnosis of mental disorders.
3. Intelligent human-computer interaction medical systems based on natural language processing, especially system modeling in the field of psychiatry.
4. The application of human posture recognition in the diagnosis of mental disorders.
5. The application of smart medical treatment in the smart mental health care system.
6. Development of a real-time patient monitoring system based on AI.
7. Application of blockchain/Internet of Things (IoT)/cloud computing/big data in the field of psychiatric medicine.
8. Construction of the medical experimental platform based on AI, especially in the field of psychiatric medicine.
9. Secure and reliable IoT, edge, and cloud services for digital healthcare.
10. Methods for processing healthcare data in edge and cloud.
11. Computation, data, and network management to facilitate IoT, edge, and cloud integration in the domain of healthcare.
12. The application of AI to mobile passive data analyses for mental health.
