Clinical trials informed framework for real world clinical implementation and deployment of artificial intelligence applications
With rapidly evolving artificial intelligence solutions, healthcare organizations need an implementation roadmap. A “clinical trials” informed approach can promote safe and impactful implementation of artificial intelligence. This framework includes four phases: (1) Safety; (2) Efficacy; (3) Effecti...
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| Published in: | NPJ digital medicine Vol. 8; no. 1; pp. 107 - 5 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
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London
Nature Publishing Group UK
17.02.2025
Nature Publishing Group Nature Portfolio |
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| ISSN: | 2398-6352, 2398-6352 |
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| Abstract | With rapidly evolving artificial intelligence solutions, healthcare organizations need an implementation roadmap. A “clinical trials” informed approach can promote safe and impactful implementation of artificial intelligence. This framework includes four phases: (1) Safety; (2) Efficacy; (3) Effectiveness and comparison to an existing standard; and (4) Monitoring. Combined with inter-institutional collaboration and national funding support, this approach will advance safe, usable, effective, and equitable deployments of artificial intelligence in healthcare. |
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| AbstractList | With rapidly evolving artificial intelligence solutions, healthcare organizations need an implementation roadmap. A "clinical trials" informed approach can promote safe and impactful implementation of artificial intelligence. This framework includes four phases: (1) Safety; (2) Efficacy; (3) Effectiveness and comparison to an existing standard; and (4) Monitoring. Combined with inter-institutional collaboration and national funding support, this approach will advance safe, usable, effective, and equitable deployments of artificial intelligence in healthcare. With rapidly evolving artificial intelligence solutions, healthcare organizations need an implementation roadmap. A "clinical trials" informed approach can promote safe and impactful implementation of artificial intelligence. This framework includes four phases: (1) Safety; (2) Efficacy; (3) Effectiveness and comparison to an existing standard; and (4) Monitoring. Combined with inter-institutional collaboration and national funding support, this approach will advance safe, usable, effective, and equitable deployments of artificial intelligence in healthcare.With rapidly evolving artificial intelligence solutions, healthcare organizations need an implementation roadmap. A "clinical trials" informed approach can promote safe and impactful implementation of artificial intelligence. This framework includes four phases: (1) Safety; (2) Efficacy; (3) Effectiveness and comparison to an existing standard; and (4) Monitoring. Combined with inter-institutional collaboration and national funding support, this approach will advance safe, usable, effective, and equitable deployments of artificial intelligence in healthcare. Abstract With rapidly evolving artificial intelligence solutions, healthcare organizations need an implementation roadmap. A “clinical trials” informed approach can promote safe and impactful implementation of artificial intelligence. This framework includes four phases: (1) Safety; (2) Efficacy; (3) Effectiveness and comparison to an existing standard; and (4) Monitoring. Combined with inter-institutional collaboration and national funding support, this approach will advance safe, usable, effective, and equitable deployments of artificial intelligence in healthcare. |
| Author | Mishuris, Rebecca G. Hernandez-Boussard, Tina Pfeffer, Michael A. Landman, Adam You, Jacqueline G. |
| Author_xml | – sequence: 1 givenname: Jacqueline G. surname: You fullname: You, Jacqueline G. email: jyou5@mgh.harvard.edu organization: Mass General Brigham, Harvard Medical School – sequence: 2 givenname: Tina surname: Hernandez-Boussard fullname: Hernandez-Boussard, Tina organization: Stanford University School of Medicine – sequence: 3 givenname: Michael A. surname: Pfeffer fullname: Pfeffer, Michael A. organization: Stanford University School of Medicine – sequence: 4 givenname: Adam surname: Landman fullname: Landman, Adam organization: Mass General Brigham, Harvard Medical School – sequence: 5 givenname: Rebecca G. surname: Mishuris fullname: Mishuris, Rebecca G. organization: Mass General Brigham, Harvard Medical School |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/39962232$$D View this record in MEDLINE/PubMed |
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| DOI | 10.1038/s41746-025-01506-4 |
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| SubjectTerms | 631/114/1305 631/114/2397 631/114/2413 692/308/409 706/703/559 Artificial intelligence Biomedicine Biotechnology Clinical medicine Clinical trials Collaboration Electronic health records Ethics FDA approval Informatics Medical equipment Medicine Medicine & Public Health Patient safety Perspective Standard of care |
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| Title | Clinical trials informed framework for real world clinical implementation and deployment of artificial intelligence applications |
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