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

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.

Authors

Institutions

Publication Details

Journal
BMC Medical Informatics and Decision Making
Published
2025-02-04
DOI
https://doi.org/10.1186/s12911-025-02883-2
Citations
6
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
3.93

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Federico Pennestrì, F. Cabitza, Giuseppe Banfi, N. Picerno
6 citations
BMC Medical Informatics and Decision Making
Artificial Intelligence in Healthcare and Education
3.93
article

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

Federico Pennestrì, F. Cabitza, Giuseppe Banfi, N. Picerno
article en
6 citations

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.

BMC Medical Informatics and Decision MakingVol. 25(1)
Vita-Salute San Raffaele University (IT), University of Milan (IT), IRCCS Ospedale Galeazzi - Sant'Ambrogio (IT), Istituti di Ricovero e Cura a Carattere Scientifico (IT), University of Milano-Bicocca (IT)
Ministero della Salute
Openalex Percentile: Top 7%
Artificial Intelligence in Healthcare and Education
3.93
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Sharing reliable information worldwide: healthcare strategies based on artificial intelligence need external validation. Position paper — Federico Pennestrì, F. Cabitza, et al. · BMC Medical Informatics and Decision Making (2025) | TGRS Research Map | TGRS