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Artificial intelligence–enabled clinical trials might be a faster way to perform rapid clinical trials and counter future pandemics: lessons learned from the COVID-19 period
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Lippincott Williams & Wilkins
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10389411/ https://www.ncbi.nlm.nih.gov/pubmed/36906740 http://dx.doi.org/10.1097/JS9.0000000000000088 |
| _version_ | 1785082293691351040 |
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| author | Chakraborty, Chiranjib Bhattacharya, Manojit Dhama, Kuldeep Agoramoorthy, Govindasamy |
| author_facet | Chakraborty, Chiranjib Bhattacharya, Manojit Dhama, Kuldeep Agoramoorthy, Govindasamy |
| author_sort | Chakraborty, Chiranjib |
| collection | PubMed |
| description | |
| format | Online Article Text |
| id | pubmed-10389411 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2023 |
| publisher | Lippincott Williams & Wilkins |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-103894112023-08-01 Artificial intelligence–enabled clinical trials might be a faster way to perform rapid clinical trials and counter future pandemics: lessons learned from the COVID-19 period Chakraborty, Chiranjib Bhattacharya, Manojit Dhama, Kuldeep Agoramoorthy, Govindasamy Int J Surg Correspondence Lippincott Williams & Wilkins 2023-03-02 /pmc/articles/PMC10389411/ /pubmed/36906740 http://dx.doi.org/10.1097/JS9.0000000000000088 Text en Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
| spellingShingle | Correspondence Chakraborty, Chiranjib Bhattacharya, Manojit Dhama, Kuldeep Agoramoorthy, Govindasamy Artificial intelligence–enabled clinical trials might be a faster way to perform rapid clinical trials and counter future pandemics: lessons learned from the COVID-19 period |
| title | Artificial intelligence–enabled clinical trials might be a faster way to perform rapid clinical trials and counter future pandemics: lessons learned from the COVID-19 period |
| title_full | Artificial intelligence–enabled clinical trials might be a faster way to perform rapid clinical trials and counter future pandemics: lessons learned from the COVID-19 period |
| title_fullStr | Artificial intelligence–enabled clinical trials might be a faster way to perform rapid clinical trials and counter future pandemics: lessons learned from the COVID-19 period |
| title_full_unstemmed | Artificial intelligence–enabled clinical trials might be a faster way to perform rapid clinical trials and counter future pandemics: lessons learned from the COVID-19 period |
| title_short | Artificial intelligence–enabled clinical trials might be a faster way to perform rapid clinical trials and counter future pandemics: lessons learned from the COVID-19 period |
| title_sort | artificial intelligence–enabled clinical trials might be a faster way to perform rapid clinical trials and counter future pandemics: lessons learned from the covid-19 period |
| topic | Correspondence |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10389411/ https://www.ncbi.nlm.nih.gov/pubmed/36906740 http://dx.doi.org/10.1097/JS9.0000000000000088 |
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