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Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paper

Articolo
Data di Pubblicazione:
2025
Citazione:
Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paper / Pennestri, F.; Cabitza, F.; Picerno, N.; Banfi, G.. - In: BMC MEDICAL INFORMATICS AND DECISION MAKING. - ISSN 1472-6947. - 25:1(2025). [10.1186/s12911-025-02883-2]
Abstract:
Training machine learning models using data from severe COVID-19 patients admitted to a central hospital, where entire wards are specifically dedicated to COVID-19, may yield predictions that differ significantly from those generated using data collected from patients admitted to a high-volume specialized hospital for orthopedic surgery, where COVID-19 is only a secondary diagnosis. This disparity arises despite the two hospitals being geographically close (within20 kilometers). While machine learning can facilitate rapid public health responses, rigorous external validation and continuous monitoring are essential to ensure reliability and safety.
Tipologia CRIS:
1.1.2. Articolo in Rivista - Letter, Note
Keywords:
Artificial intelligence; External validation; Machine learning; Orthopedics; Patient stratification; Techno-vigilance
Elenco autori:
Pennestri, F.; Cabitza, F.; Picerno, N.; Banfi, G.
Autori di Ateneo:
BANFI GIUSEPPE
Link alla scheda completa:
https://iris.unisr.it/handle/20.500.11768/199339
Pubblicato in:
BMC MEDICAL INFORMATICS AND DECISION MAKING
Journal
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