Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paper
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-vol...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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BMC
2025-02-01
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| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12911-025-02883-2 |
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| _version_ | 1823861958117425152 |
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| author | F. Pennestrì F. Cabitza N. Picerno G. Banfi |
| author_facet | F. Pennestrì F. Cabitza N. Picerno G. Banfi |
| author_sort | F. Pennestrì |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-48ea63672ef2485ab610c74f6e42255b |
| institution | Kabale University |
| issn | 1472-6947 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Informatics and Decision Making |
| spelling | doaj-art-48ea63672ef2485ab610c74f6e42255b2025-02-09T12:40:23ZengBMCBMC Medical Informatics and Decision Making1472-69472025-02-012511410.1186/s12911-025-02883-2Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paperF. Pennestrì0F. Cabitza1N. Picerno2G. Banfi3Direzione Scientifica, IRCCS Istituto Ortopedico GaleazziDirezione Scientifica, IRCCS Istituto Ortopedico GaleazziDirezione Scientifica, IRCCS Istituto Ortopedico GaleazziDirezione Scientifica, IRCCS Istituto Ortopedico GaleazziAbstract 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.https://doi.org/10.1186/s12911-025-02883-2Artificial intelligenceExternal validationMachine learningOrthopedicsPatient stratificationTechno-vigilance |
| spellingShingle | F. Pennestrì F. Cabitza N. Picerno G. Banfi Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paper BMC Medical Informatics and Decision Making Artificial intelligence External validation Machine learning Orthopedics Patient stratification Techno-vigilance |
| title | Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paper |
| title_full | Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paper |
| title_fullStr | Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paper |
| title_full_unstemmed | Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paper |
| title_short | Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paper |
| title_sort | sharing reliable information worldwide healthcare strategies based on artificial intelligence need external validation position paper |
| topic | Artificial intelligence External validation Machine learning Orthopedics Patient stratification Techno-vigilance |
| url | https://doi.org/10.1186/s12911-025-02883-2 |
| work_keys_str_mv | AT fpennestri sharingreliableinformationworldwidehealthcarestrategiesbasedonartificialintelligenceneedexternalvalidationpositionpaper AT fcabitza sharingreliableinformationworldwidehealthcarestrategiesbasedonartificialintelligenceneedexternalvalidationpositionpaper AT npicerno sharingreliableinformationworldwidehealthcarestrategiesbasedonartificialintelligenceneedexternalvalidationpositionpaper AT gbanfi sharingreliableinformationworldwidehealthcarestrategiesbasedonartificialintelligenceneedexternalvalidationpositionpaper |