Diagnostic uncertainty calibration: towards reliable machine predictions in medical domain


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<meta name="Description" CONTENT="Artificial Intelligence Journal" />
<meta name="r0identifier" content="5f28cd89d8b22d05e145c722a304e1c6" />
RxRegistration ID
R0Hash MD5 (of R3):5f28cd89d8b22d05e145c722a304e1c6
R1Registration number (in the domain editorialia.com at WordPress):dmeditorialiawp.14402
R2Date-p-order (ddmmyyyypx):19072020p1
R3Cid (combined id R1+R2):dmeditorialiawp.1440219072020p1
R4Resource official title:Diagnostic Uncertainty Calibration: Towards Reliable Machine Predictions in Medical Domain
R5Publisher:arXiv.org
R6Resource website (1) ( #OpenAccess | #Openscience ):arxiv.org/abs/2007.01659v2
R9DOI:arXiv:2007.01659v2
R12Authors (separated by commas):Takahiro Mimori, Keiko Sasada, Hirotaka Matsui, Issei Sato
R14Keyword (selected 1 among the labels applied to this entry):=medicine
R15QR code (of the linked url at WP):La imagen tiene un atributo ALT vacío; su nombre de archivo es qr.png
R16Time stamp URL:
R17Digital signature URL:Pending signature

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