Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385576061> ?p ?o ?g. }
- W4385576061 endingPage "2199" @default.
- W4385576061 startingPage "2199" @default.
- W4385576061 abstract "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." @default.
- W4385576061 created "2023-08-05" @default.
- W4385576061 creator A5009770666 @default.
- W4385576061 creator A5018146563 @default.
- W4385576061 creator A5022725761 @default.
- W4385576061 creator A5039490047 @default.
- W4385576061 creator A5053599061 @default.
- W4385576061 creator A5062830911 @default.
- W4385576061 creator A5065509286 @default.
- W4385576061 creator A5066933655 @default.
- W4385576061 creator A5077368544 @default.
- W4385576061 creator A5088016953 @default.
- W4385576061 creator A5088978718 @default.
- W4385576061 date "2023-08-04" @default.
- W4385576061 modified "2023-10-01" @default.
- W4385576061 title "CADUCEO: A Platform to Support Federated Healthcare Facilities through Artificial Intelligence" @default.
- W4385576061 cites W1537066827 @default.
- W4385576061 cites W2024959214 @default.
- W4385576061 cites W2033115336 @default.
- W4385576061 cites W2034841618 @default.
- W4385576061 cites W2069143585 @default.
- W4385576061 cites W2134086158 @default.
- W4385576061 cites W2162210260 @default.
- W4385576061 cites W2164330572 @default.
- W4385576061 cites W2220275977 @default.
- W4385576061 cites W2282821441 @default.
- W4385576061 cites W2293037920 @default.
- W4385576061 cites W2371884860 @default.
- W4385576061 cites W2506743715 @default.
- W4385576061 cites W2510374233 @default.
- W4385576061 cites W2524620548 @default.
- W4385576061 cites W2592929672 @default.
- W4385576061 cites W2604262106 @default.
- W4385576061 cites W2734784508 @default.
- W4385576061 cites W2782436336 @default.
- W4385576061 cites W2783522756 @default.
- W4385576061 cites W2793745122 @default.
- W4385576061 cites W2800769566 @default.
- W4385576061 cites W2891503716 @default.
- W4385576061 cites W2913926073 @default.
- W4385576061 cites W2922073769 @default.
- W4385576061 cites W2949736877 @default.
- W4385576061 cites W2954996726 @default.
- W4385576061 cites W2958089299 @default.
- W4385576061 cites W2963037989 @default.
- W4385576061 cites W2963183964 @default.
- W4385576061 cites W2969944904 @default.
- W4385576061 cites W2975495759 @default.
- W4385576061 cites W2977072935 @default.
- W4385576061 cites W2977942577 @default.
- W4385576061 cites W2981731882 @default.
- W4385576061 cites W2992511782 @default.
- W4385576061 cites W2996845627 @default.
- W4385576061 cites W2997428643 @default.
- W4385576061 cites W3011591403 @default.
- W4385576061 cites W3016632787 @default.
- W4385576061 cites W3021503072 @default.
- W4385576061 cites W3027885821 @default.
- W4385576061 cites W3028537074 @default.
- W4385576061 cites W3035574324 @default.
- W4385576061 cites W3044197051 @default.
- W4385576061 cites W3045168954 @default.
- W4385576061 cites W3045674654 @default.
- W4385576061 cites W3046115333 @default.
- W4385576061 cites W3046474724 @default.
- W4385576061 cites W3096831136 @default.
- W4385576061 cites W3100789280 @default.
- W4385576061 cites W3105081694 @default.
- W4385576061 cites W3131705220 @default.
- W4385576061 cites W3163842339 @default.
- W4385576061 cites W3166664106 @default.
- W4385576061 cites W3171873561 @default.
- W4385576061 cites W3174867786 @default.
- W4385576061 cites W3176923149 @default.
- W4385576061 cites W3178709966 @default.
- W4385576061 cites W3182080444 @default.
- W4385576061 cites W3183452672 @default.
- W4385576061 cites W4206348828 @default.
- W4385576061 cites W4214717370 @default.
- W4385576061 cites W4226366304 @default.
- W4385576061 cites W4226484282 @default.
- W4385576061 cites W4283756152 @default.
- W4385576061 cites W4288685354 @default.
- W4385576061 cites W4289828999 @default.
- W4385576061 cites W4295443626 @default.
- W4385576061 cites W4296334467 @default.
- W4385576061 cites W4296984381 @default.
- W4385576061 cites W4300337452 @default.
- W4385576061 cites W4319300595 @default.
- W4385576061 cites W4322102698 @default.
- W4385576061 cites W4378171892 @default.
- W4385576061 doi "https://doi.org/10.3390/healthcare11152199" @default.
- W4385576061 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37570439" @default.
- W4385576061 hasPublicationYear "2023" @default.
- W4385576061 type Work @default.
- W4385576061 citedByCount "1" @default.
- W4385576061 countsByYear W43855760612023 @default.
- W4385576061 crossrefType "journal-article" @default.