Assessing the feasibility of large language models to identify top research priorities in enhanced external counterpulsation.
Enhanced External Counterpulsation (EECP), as a non-invasive, cost-effective, and efficient adjunctive circulatory technique, has been widely applied in in the cardiovascular field. Numerous studies and clinical observations have confirmed the obvious advantages of EECP in promoting blood flow perfu...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0305442 |
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| _version_ | 1849309931789877248 |
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| author | Shengkun Gai Fangwan Huang Xuanyun Liu Ryan G Benton Glen M Borchert Jingshan Huang Xiuyu Leng |
| author_facet | Shengkun Gai Fangwan Huang Xuanyun Liu Ryan G Benton Glen M Borchert Jingshan Huang Xiuyu Leng |
| author_sort | Shengkun Gai |
| collection | DOAJ |
| description | Enhanced External Counterpulsation (EECP), as a non-invasive, cost-effective, and efficient adjunctive circulatory technique, has been widely applied in in the cardiovascular field. Numerous studies and clinical observations have confirmed the obvious advantages of EECP in promoting blood flow perfusion to vital organs such as the heart, brain, and kidneys. However, many potential mechanisms of EECP remain insufficiently validated, necessitating researchers to dedicate substantial time and effort to in-depth investigations. In this work, large language models (such as ChatGPT and Ernie Bot) were used to identify top research priorities in five key topics in the field of EECP: mechanisms, device improvements, cardiovascular applications, neurological applications, and other applications. After generating specific research priorities in each domain through language models, a panel of nine experienced EECP experts was invited to independently evaluate and score them based on four parameters: relevance, originality, clarity, and specificity. Notably, high average and median scores for these evaluation parameters were obtained, indicating a strong endorsement from experts in the EECP field. This study preliminarily suggests that large language models like ChatGPT and Ernie Bot could serve as powerful tools for identifying and prioritizing research priorities in the EECP domain. |
| format | Article |
| id | doaj-art-035cd7cf10074e4f94aee4068613d248 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-035cd7cf10074e4f94aee4068613d2482025-08-20T03:53:56ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01204e030544210.1371/journal.pone.0305442Assessing the feasibility of large language models to identify top research priorities in enhanced external counterpulsation.Shengkun GaiFangwan HuangXuanyun LiuRyan G BentonGlen M BorchertJingshan HuangXiuyu LengEnhanced External Counterpulsation (EECP), as a non-invasive, cost-effective, and efficient adjunctive circulatory technique, has been widely applied in in the cardiovascular field. Numerous studies and clinical observations have confirmed the obvious advantages of EECP in promoting blood flow perfusion to vital organs such as the heart, brain, and kidneys. However, many potential mechanisms of EECP remain insufficiently validated, necessitating researchers to dedicate substantial time and effort to in-depth investigations. In this work, large language models (such as ChatGPT and Ernie Bot) were used to identify top research priorities in five key topics in the field of EECP: mechanisms, device improvements, cardiovascular applications, neurological applications, and other applications. After generating specific research priorities in each domain through language models, a panel of nine experienced EECP experts was invited to independently evaluate and score them based on four parameters: relevance, originality, clarity, and specificity. Notably, high average and median scores for these evaluation parameters were obtained, indicating a strong endorsement from experts in the EECP field. This study preliminarily suggests that large language models like ChatGPT and Ernie Bot could serve as powerful tools for identifying and prioritizing research priorities in the EECP domain.https://doi.org/10.1371/journal.pone.0305442 |
| spellingShingle | Shengkun Gai Fangwan Huang Xuanyun Liu Ryan G Benton Glen M Borchert Jingshan Huang Xiuyu Leng Assessing the feasibility of large language models to identify top research priorities in enhanced external counterpulsation. PLoS ONE |
| title | Assessing the feasibility of large language models to identify top research priorities in enhanced external counterpulsation. |
| title_full | Assessing the feasibility of large language models to identify top research priorities in enhanced external counterpulsation. |
| title_fullStr | Assessing the feasibility of large language models to identify top research priorities in enhanced external counterpulsation. |
| title_full_unstemmed | Assessing the feasibility of large language models to identify top research priorities in enhanced external counterpulsation. |
| title_short | Assessing the feasibility of large language models to identify top research priorities in enhanced external counterpulsation. |
| title_sort | assessing the feasibility of large language models to identify top research priorities in enhanced external counterpulsation |
| url | https://doi.org/10.1371/journal.pone.0305442 |
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