Con: Artificial Intelligence-Derived Algorithms to Guide Perioperative Blood Management Decision Making.
J Cardiothorac Vasc Anesth
; 37(10): 2145-2147, 2023 10.
Article
em En
| MEDLINE
| ID: mdl-37217426
Artificial intelligence has the potential to improve the care that is given to patients; however, the predictive models created are only as good as the base data used in their design. Perioperative blood management presents a complex clinical conundrum in which significant variability and the unstructured nature of the required data make it difficult to develop precise prediction models. There is a potential need for training clinicians to ensure they can interrogate the system and override when errors occur. Current systems created to predict perioperative blood transfusion are not generalizable across clinical settings, and there is a considerable cost implication required to research and develop artificial intelligence systems that would disadvantage resource-poor health systems. In addition, a lack of strong regulation currently means it is difficult to prevent bias.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Inteligência Artificial
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article