About this Research Topic
OpenAI has recently released GPT-4 (or called ChatGPT plus), which represents one small step for generative AI (GAI), but one giant step for artificial general intelligence (AGI). The capabilities of ChatGPT in the medical field have been already assessed in several works, such as cirrhosis and hepatocellular carcinoma (HCC) diagnosis and prevention, and answering frequently asked questions about diabetes. In a study conducted to identify appropriate imaging for patients requiring breast cancer screening and assessment for breast pain, it was exciting to find that ChatGPT achieved an accuracy of 56.25% even with the worst-performing set of metrics, when assessing whether the proposed imaging modality complies with the American College of Radiology (ACR) guidelines.
As to the psychiatric field, current ChatGPT uses have been mainly limited to assisting psychiatrists with clinical routine tasks, while tasks of screening and diagnosis, psychotherapy, or patient assessments are still commonly performed by trained therapists. Although various trials of ChatGPT-assisted mental health services have been pursued, such as ChatBeacon, an all-inclusive customer service platform providing mental health assistance powered by ChatGPT; and Koko, a free therapy program testing a demo of GPT-3 mental health intervention, current discussion about the potential uses of AGI in psychiatry is still quite limited. As AGI, especially GPT-like technologies, gains more power and efficiency, we can foresee that there will be increasing directions to further integrate and expand AGI applications in clinical psychiatry in the near future.
For example, ChatGPT may help deal with the burnout issue encountered by psychiatrists in psychiatric clinics, by assisting in processing transcripts of clinical dictations to generate summaries from medical dialogues and then entering into medical records as admission notes. ChatGPT can also help complete medical record documentation in standard or customized formats to reduce stressful bureaucracy and protect mental health professionals from burnout. On the other hand, ChatGPT may also facilitate the communication process between psychiatrists with other doctors and healthcare professionals by providing templates or polishing the contents in consultation letters, notes, and other clinical communications; as well as communication between patients and psychiatrists by generating appropriate patient clinic letters with humanity.
Despite continuous advances in the GPT model, we must consider significant ethical challenges for widespread application in psychiatry and healthcare. For example, advanced GPT-4 model still has potential risks of providing harmful advices due to the fluid nature of language and associated training data sets. Therefore, before commercial release, extensive training, adjustments, and comprehensive evaluation of a fully-automated psychotherapy system should be conducted to minimize the risk of harm to patients. Furthermore, it should be mandatory and necessary for mental health professionals to adopt a safer supervision operational mode when using AI systems as assistants, through routine monitoring of patients and identifying the erroneous performance of AI systems. Like many other past technological advances introduced in health care, GPT technology is envisioned to enhance the professional team’s capabilities to deliver more efficient and effective care only after much validation and real-world testing. Therefore, it is essential for researchers to re-examine issues such as professional and ethical standards in patient-physician relationships, and to construct new diagnostic, therapeutic, and training models that incorporate digital health care into clinical practice.
Based on all the discussion above, we propose this Research Topic, mainly aiming to provide an updated status of AI in the field of psychiatry and envision a potential future of digital mental health care via integration and advances in AGI technology and its supporting devices such as knowledge tree and hardware, etc. We especially welcome the studies dedicated to exploring the use of the technologies in depression and related disorders, which afflict a huge population and also desperately need technological improvements in effective treatments.
The papers of our interest include any AI/AGI-related paper on depression and related disorders, which can be reviews, original reports, commentaries or hypotheses.
As to the psychiatric field, current ChatGPT uses have been mainly limited to assisting psychiatrists with clinical routine tasks, while tasks of screening and diagnosis, psychotherapy, or patient assessments are still commonly performed by trained therapists. Although various trials of ChatGPT-assisted mental health services have been pursued, such as ChatBeacon, an all-inclusive customer service platform providing mental health assistance powered by ChatGPT; and Koko, a free therapy program testing a demo of GPT-3 mental health intervention, current discussion about the potential uses of AGI in psychiatry is still quite limited. As AGI, especially GPT-like technologies, gains more power and efficiency, we can foresee that there will be increasing directions to further integrate and expand AGI applications in clinical psychiatry in the near future.
For example, ChatGPT may help deal with the burnout issue encountered by psychiatrists in psychiatric clinics, by assisting in processing transcripts of clinical dictations to generate summaries from medical dialogues and then entering into medical records as admission notes. ChatGPT can also help complete medical record documentation in standard or customized formats to reduce stressful bureaucracy and protect mental health professionals from burnout. On the other hand, ChatGPT may also facilitate the communication process between psychiatrists with other doctors and healthcare professionals by providing templates or polishing the contents in consultation letters, notes, and other clinical communications; as well as communication between patients and psychiatrists by generating appropriate patient clinic letters with humanity.
Despite continuous advances in the GPT model, we must consider significant ethical challenges for widespread application in psychiatry and healthcare. For example, advanced GPT-4 model still has potential risks of providing harmful advices due to the fluid nature of language and associated training data sets. Therefore, before commercial release, extensive training, adjustments, and comprehensive evaluation of a fully-automated psychotherapy system should be conducted to minimize the risk of harm to patients. Furthermore, it should be mandatory and necessary for mental health professionals to adopt a safer supervision operational mode when using AI systems as assistants, through routine monitoring of patients and identifying the erroneous performance of AI systems. Like many other past technological advances introduced in health care, GPT technology is envisioned to enhance the professional team’s capabilities to deliver more efficient and effective care only after much validation and real-world testing. Therefore, it is essential for researchers to re-examine issues such as professional and ethical standards in patient-physician relationships, and to construct new diagnostic, therapeutic, and training models that incorporate digital health care into clinical practice.
Based on all the discussion above, we propose this Research Topic, mainly aiming to provide an updated status of AI in the field of psychiatry and envision a potential future of digital mental health care via integration and advances in AGI technology and its supporting devices such as knowledge tree and hardware, etc. We especially welcome the studies dedicated to exploring the use of the technologies in depression and related disorders, which afflict a huge population and also desperately need technological improvements in effective treatments.
The papers of our interest include any AI/AGI-related paper on depression and related disorders, which can be reviews, original reports, commentaries or hypotheses.
Keywords: Artificial Intelligence, Digital Medicine, Psychiatry, ChatGPT, Big-data, Foundation Model, Depression.
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