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  2. Barucci A, Neri E. Adversarial radiomics: the rising of potential risks in medical imaging from adversarial learning. Eur J Nucl Med Mol Imaging. 2020 Dec;47(13):2941-2943. doi:10.1007/s00259-020-04879-8. PMID: 32451605.
  3. Coppola F, Faggioni L, Regge D, Giovagnoni A, Golfieri R, Bibbolino C, Miele V, Neri E, Grassi R. Artificial intelligence: radiologists’ expectations and opinions gleaned from a nationwide online survey. Radiol Med. 2020 Apr 29. doi:10.1007/s11547-020-01205-y. Epub ahead of print. PMID: 32350797
  4. Brady AP, Neri E. Artificial Intelligence in Radiology-Ethical Considerations. Diagnostics (Basel). 2020 Apr 17;10(4):231. doi:10.3390/diagnostics10040231. PMID: 32316503; PMCID: PMC7235856.
  5. Neri E, Coppola F, Miele V, Bibbolino C, Grassi R. Artificial intelligence: Who is responsible for the diagnosis? Radiol Med. 2020 Jun;125(6):517-521. doi: 10.1007/s11547-020-01135-9. Epub 2020 Jan 31. PMID: 32006241
  6. Neri E, Del Re M, Paiar F, Erba P, Cocuzza P, Regge D, Danesi R. Radiomics and liquid biopsy in oncology: the holons of systems medicine. Insights Imaging. 2018 Dec;9(6):915-924. doi:10.1007/s13244-018-0657-7. Epub 2018 Nov 14. PMID:30430428; PMCID: PMC6269342.
  7. Usefulness of MRI-based radiomic features for distinguishing Warthin tumor from pleomorphic adenoma: performance assessment using T2-weighted and post-contrast T1-weighted MR images.
    Faggioni L, Gabelloni M, De Vietro F, Frey J, Mendola V, Cavallero D, Borgheresi R, Tumminello L, Shortrede J, Morganti R, Seccia V, Coppola F, Cioni D, Neri E.
    Eur J Radiol Open. 2022 Jun 18;9:100429. doi: 10.1016/j.ejro.2022.100429. eCollection 2022.
    PMID: 35757232 Free PMC article.
  8. How to Assess Trustworthy AI in Practice. 
    Cite as: arXiv:2206.09887 [cs.CY]. [v2] Tue, 28 Jun 2022 14:23:47 UTC (465 KB) .
    The full report is available on arXiv 
    You can download the full report as .PDF