From Big Data's 5Vs to clinical practice's 5Ws: enhancing data-driven decision making in healthcare.
Artificial intelligence
Clinical practise
Machine learning
Perioperative medicine
Journal
Journal of clinical monitoring and computing
ISSN: 1573-2614
Titre abrégé: J Clin Monit Comput
Pays: Netherlands
ID NLM: 9806357
Informations de publication
Date de publication:
10 2023
10 2023
Historique:
received:
25
01
2023
accepted:
01
04
2023
medline:
27
9
2023
pubmed:
25
4
2023
entrez:
25
4
2023
Statut:
ppublish
Résumé
The use of AI-based algorithms is rapidly growing in healthcare, but there is still an ongoing debate about how to manage and ensure accountability for their clinical use. While most of the studies focus on demonstrating a good algorithm performance it is important to acknowledge that several additional steps are needed for reaching an effective implementation of AI-based models in daily clinical practice, with implementation being one of the main key factors. We propose a model characterized by five questions that can guide in this process. Additionally, we believe that a hybrid intelligence, human and artificial respectively, is the new clinical paradigm that offer the most benefits for developing clinical decision support systems for bedside use.
Identifiants
pubmed: 37097338
doi: 10.1007/s10877-023-01007-3
pii: 10.1007/s10877-023-01007-3
doi:
Types de publication
Letter
Langues
eng
Sous-ensembles de citation
IM
Pagination
1423-1425Informations de copyright
© 2023. The Author(s), under exclusive licence to Springer Nature B.V.
Références
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