Current Status and Future Directions of Artificial Intelligence in Post-Traumatic Stress Disorder: A Literature Measurement Analysis
This study aims to explore the current state of research and the applicability of artificial intelligence (AI) at various stages of post-traumatic stress disorder (PTSD), including prevention, diagnosis, treatment, patient self-management, and drug development. We conducted a bibliometric analysis u...
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2024-12-01
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| author | Ruoyu Wan Ruohong Wan Qing Xie Anshu Hu Wei Xie Junjie Chen Yuhan Liu |
| author_facet | Ruoyu Wan Ruohong Wan Qing Xie Anshu Hu Wei Xie Junjie Chen Yuhan Liu |
| author_sort | Ruoyu Wan |
| collection | DOAJ |
| description | This study aims to explore the current state of research and the applicability of artificial intelligence (AI) at various stages of post-traumatic stress disorder (PTSD), including prevention, diagnosis, treatment, patient self-management, and drug development. We conducted a bibliometric analysis using software tools such as Bibliometrix (version 4.1), VOSviewer (version 1.6.19), and CiteSpace (version 6.3.R1) on the relevant literature from the Web of Science Core Collection (WoSCC). The analysis reveals a significant increase in publications since 2017. Kerry J. Ressler has emerged as the most influential author in the field to date. The United States leads in the number of publications, producing seven times more papers than Canada, the second-ranked country, and demonstrating substantial influence. Harvard University and the Veterans Health Administration are also key institutions in this field. The <i>Journal of Affective Disorders</i> has the highest number of publications and impact in this area. In recent years, keywords related to functional connectivity, risk factors, and algorithm development have gained prominence. The field holds immense research potential, with AI poised to revolutionize PTSD management through early symptom detection, personalized treatment plans, and continuous patient monitoring. However, there are numerous challenges, and fully realizing AI’s potential will require overcoming hurdles in algorithm design, data integration, and societal ethics. To promote more extensive and in-depth future research, it is crucial to prioritize the development of standardized protocols for AI implementation, foster interdisciplinary collaboration—especially between AI and neuroscience—and address public concerns about AI’s role in healthcare to enhance its acceptance and effectiveness. |
| format | Article |
| id | doaj-art-7b55b810585849979246d4b572ec8d93 |
| institution | Kabale University |
| issn | 2076-328X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Behavioral Sciences |
| spelling | doaj-art-7b55b810585849979246d4b572ec8d932025-01-24T13:22:39ZengMDPI AGBehavioral Sciences2076-328X2024-12-011512710.3390/bs15010027Current Status and Future Directions of Artificial Intelligence in Post-Traumatic Stress Disorder: A Literature Measurement AnalysisRuoyu Wan0Ruohong Wan1Qing Xie2Anshu Hu3Wei Xie4Junjie Chen5Yuhan Liu6Department of Digital Media Art, School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan 430074, ChinaAcademy of Arts & Design, Tsinghua University, Beijing 100084, ChinaSchool of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan 430070, ChinaSchool of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan 430070, ChinaDepartment of Digital Media Art, School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan 430074, ChinaDepartment of Digital Media Art, School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan 430074, ChinaDepartment of Digital Media Art, School of Architecture and Urban Planning, Huazhong University of Science and Technology, Wuhan 430074, ChinaThis study aims to explore the current state of research and the applicability of artificial intelligence (AI) at various stages of post-traumatic stress disorder (PTSD), including prevention, diagnosis, treatment, patient self-management, and drug development. We conducted a bibliometric analysis using software tools such as Bibliometrix (version 4.1), VOSviewer (version 1.6.19), and CiteSpace (version 6.3.R1) on the relevant literature from the Web of Science Core Collection (WoSCC). The analysis reveals a significant increase in publications since 2017. Kerry J. Ressler has emerged as the most influential author in the field to date. The United States leads in the number of publications, producing seven times more papers than Canada, the second-ranked country, and demonstrating substantial influence. Harvard University and the Veterans Health Administration are also key institutions in this field. The <i>Journal of Affective Disorders</i> has the highest number of publications and impact in this area. In recent years, keywords related to functional connectivity, risk factors, and algorithm development have gained prominence. The field holds immense research potential, with AI poised to revolutionize PTSD management through early symptom detection, personalized treatment plans, and continuous patient monitoring. However, there are numerous challenges, and fully realizing AI’s potential will require overcoming hurdles in algorithm design, data integration, and societal ethics. To promote more extensive and in-depth future research, it is crucial to prioritize the development of standardized protocols for AI implementation, foster interdisciplinary collaboration—especially between AI and neuroscience—and address public concerns about AI’s role in healthcare to enhance its acceptance and effectiveness.https://www.mdpi.com/2076-328X/15/1/27artificial intelligencealgorithmbibliometric analysisBibliometrixCiteSpacedigital psychiatry |
| spellingShingle | Ruoyu Wan Ruohong Wan Qing Xie Anshu Hu Wei Xie Junjie Chen Yuhan Liu Current Status and Future Directions of Artificial Intelligence in Post-Traumatic Stress Disorder: A Literature Measurement Analysis Behavioral Sciences artificial intelligence algorithm bibliometric analysis Bibliometrix CiteSpace digital psychiatry |
| title | Current Status and Future Directions of Artificial Intelligence in Post-Traumatic Stress Disorder: A Literature Measurement Analysis |
| title_full | Current Status and Future Directions of Artificial Intelligence in Post-Traumatic Stress Disorder: A Literature Measurement Analysis |
| title_fullStr | Current Status and Future Directions of Artificial Intelligence in Post-Traumatic Stress Disorder: A Literature Measurement Analysis |
| title_full_unstemmed | Current Status and Future Directions of Artificial Intelligence in Post-Traumatic Stress Disorder: A Literature Measurement Analysis |
| title_short | Current Status and Future Directions of Artificial Intelligence in Post-Traumatic Stress Disorder: A Literature Measurement Analysis |
| title_sort | current status and future directions of artificial intelligence in post traumatic stress disorder a literature measurement analysis |
| topic | artificial intelligence algorithm bibliometric analysis Bibliometrix CiteSpace digital psychiatry |
| url | https://www.mdpi.com/2076-328X/15/1/27 |
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