Evaluating the Feasibility of ChatGPT in Healthcare: An Analysis of Multiple Clinical and Research Scenarios.
Saved in:
| Title: | Evaluating the Feasibility of ChatGPT in Healthcare: An Analysis of Multiple Clinical and Research Scenarios. |
|---|---|
| Authors: | Cascella, Marco1 (AUTHOR), Montomoli, Jonathan2 (AUTHOR), Bellini, Valentina3 (AUTHOR), Bignami, Elena3 (AUTHOR) elenagiovanna.bignami@unipr.it |
| Source: | Journal of Medical Systems. Dec2023, Vol. 47 Issue 1, p1-5. 5p. |
| Abstract: | This paper aims to highlight the potential applications and limits of a large language model (LLM) in healthcare. ChatGPT is a recently developed LLM that was trained on a massive dataset of text for dialogue with users. Although AI-based language models like ChatGPT have demonstrated impressive capabilities, it is uncertain how well they will perform in real-world scenarios, particularly in fields such as medicine where high-level and complex thinking is necessary. Furthermore, while the use of ChatGPT in writing scientific articles and other scientific outputs may have potential benefits, important ethical concerns must also be addressed. Consequently, we investigated the feasibility of ChatGPT in clinical and research scenarios: (1) support of the clinical practice, (2) scientific production, (3) misuse in medicine and research, and (4) reasoning about public health topics. Results indicated that it is important to recognize and promote education on the appropriate use and potential pitfalls of AI-based LLMs in medicine. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Medical Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 162248356 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Evaluating the Feasibility of ChatGPT in Healthcare: An Analysis of Multiple Clinical and Research Scenarios. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Cascella%2C+Marco%22">Cascella, Marco</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Montomoli%2C+Jonathan%22">Montomoli, Jonathan</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bellini%2C+Valentina%22">Bellini, Valentina</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bignami%2C+Elena%22">Bignami, Elena</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> elenagiovanna.bignami@unipr.it</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Medical+Systems%22">Journal of Medical Systems</searchLink>. Dec2023, Vol. 47 Issue 1, p1-5. 5p. – Name: Abstract Label: Abstract Group: Ab Data: This paper aims to highlight the potential applications and limits of a large language model (LLM) in healthcare. ChatGPT is a recently developed LLM that was trained on a massive dataset of text for dialogue with users. Although AI-based language models like ChatGPT have demonstrated impressive capabilities, it is uncertain how well they will perform in real-world scenarios, particularly in fields such as medicine where high-level and complex thinking is necessary. Furthermore, while the use of ChatGPT in writing scientific articles and other scientific outputs may have potential benefits, important ethical concerns must also be addressed. Consequently, we investigated the feasibility of ChatGPT in clinical and research scenarios: (1) support of the clinical practice, (2) scientific production, (3) misuse in medicine and research, and (4) reasoning about public health topics. Results indicated that it is important to recognize and promote education on the appropriate use and potential pitfalls of AI-based LLMs in medicine. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Medical Systems is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=162248356 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s10916-023-01925-4 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 5 StartPage: 1 Titles: – TitleFull: Evaluating the Feasibility of ChatGPT in Healthcare: An Analysis of Multiple Clinical and Research Scenarios. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Cascella, Marco – PersonEntity: Name: NameFull: Montomoli, Jonathan – PersonEntity: Name: NameFull: Bellini, Valentina – PersonEntity: Name: NameFull: Bignami, Elena IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2023 Type: published Y: 2023 Identifiers: – Type: issn-print Value: 01485598 Numbering: – Type: volume Value: 47 – Type: issue Value: 1 Titles: – TitleFull: Journal of Medical Systems Type: main |
| ResultId | 1 |
