CADUCEO: A Platform to Support Federated Healthcare Facilities through Artificial Intelligence.
artificial intelligence
deep learning
e-health
Journal
Healthcare (Basel, Switzerland)
ISSN: 2227-9032
Titre abrégé: Healthcare (Basel)
Pays: Switzerland
ID NLM: 101666525
Informations de publication
Date de publication:
04 Aug 2023
04 Aug 2023
Historique:
received:
13
07
2023
revised:
26
07
2023
accepted:
31
07
2023
medline:
12
8
2023
pubmed:
12
8
2023
entrez:
12
8
2023
Statut:
epublish
Résumé
Data-driven algorithms have proven to be effective for a variety of medical tasks, including disease categorization and prediction, personalized medicine design, and imaging diagnostics. Although their performance is frequently on par with that of clinicians, their widespread use is constrained by a number of obstacles, including the requirement for high-quality data that are typical of the population, the difficulty of explaining how they operate, and ethical and regulatory concerns. The use of data augmentation and synthetic data generation methodologies, such as federated learning and explainable artificial intelligence ones, could provide a viable solution to the current issues, facilitating the widespread application of artificial intelligence algorithms in the clinical application domain and reducing the time needed for prevention, diagnosis, and prognosis by up to 70%. To this end, a novel AI-based functional framework is conceived and presented in this paper.
Identifiants
pubmed: 37570439
pii: healthcare11152199
doi: 10.3390/healthcare11152199
pmc: PMC10418332
pii:
doi:
Types de publication
Journal Article
Langues
eng
Subventions
Organisme : Italian Ministry of Enterprises and Made in Italy
ID : F/180025/01-05/X43
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