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ChatGPT and mental ...
ChatGPT and mental healthcare : balancing benefits with risks of harms
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- Blease, Charlotte (författare)
- Uppsala universitet,E-hälsa och hälsodata,Harvard Med Sch, Beth Israel Deaconess Med Ctr, Digital Psychiat, Boston, MA USA.
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- Torous, John (författare)
- Harvard Med Sch, Beth Israel Deaconess Med Ctr, Psychiat, Boston, MA USA.
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(creator_code:org_t)
- BMJ Publishing Group Ltd, 2023
- 2023
- Engelska.
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Ingår i: BMJ Mental Health. - : BMJ Publishing Group Ltd. - 2755-9734. ; 26:1
- Relaterad länk:
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https://doi.org/10.1...
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https://uu.diva-port... (primary) (Raw object)
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Abstract
Ämnesord
Stäng
- Against the global need for increased access to mental services, health organisations are looking to technological advances to improve the delivery of care and lower costs. Since November 2022, with the public launch of OpenAI's ChatGPT, the field of generative artificial intelligence (AI) has received expanding attention. Although generative AI itself is not new, technical advances and the increased accessibility of large language models (LLMs) (eg, OpenAI's GPT-4 and Google's Bard) suggest use of these tools could be clinically significant. LLMs are an application of generative AI technology that can summarise and generate content based on training on vast data sets. Unlike search engines, which provide internet links in response to typed entries, chatbots that rely on generative language models can simulate dialogue that resembles human conversations. We examine the potential promise and the risks of using LLMs in mental healthcare today, focusing on their scope to impact mental healthcare, including global equity in the delivery of care. Although we caution that LLMs should not be used to disintermediate mental health clinicians, we signal how-if carefully implemented-in the long term these tools could reap benefits for patients and health professionals.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Psykiatri (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Psychiatry (hsv//eng)
Nyckelord
- Machine Learning
- Depression & mood disorders
- Adult psychiatry
Publikations- och innehållstyp
- vet (ämneskategori)
- art (ämneskategori)
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