02664nam a22004815i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050001200172072001600184072002300200072001500223100008200238245012900320250001800449264007500467300004600542336002600588337002600614338003600640347002400676505029700700520075500997650002101752650002401773650003201797650002901829650002601858650002201884650002401906650002901930710003401959773002601993776003602019776003602055856004602091912001402137912001402151999001702165978-3-031-47194-0DE-He21320251030110916.0cr nn 008mamaa240108s2024    sz |    s    |||| 0|eng d  a97830314719409978-3-031-47194-07 a10.1007/978-3-031-47194-02doi 4aQH323.5 7aPBT2bicssc 7aMED0900002bisacsh 7aPBT2thema1 aLarner, A. J.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut96932014aThe 2x2 Matrixh[electronic resource] :bContingency, Confusion and the Metrics of Binary Classification /cby A. J. Larner.  a2nd ed. 2024. 1aCham :bSpringer International Publishing :bImprint: Springer,c2024.  aXVIII, 252 p. 55 illus.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda0 aIntroduction -- Paired measures -- Paired complementary measures -- Unitary measures -- Number needed (reciprocal) measures and their combinations as likelihoods -- Quality (Q) measures -- Graphing methods -- Other measures, other tables -- Classification of metrics of binary classification.  aThis book describes, extends, and illustrates the metrics of binary classification through worked examples. Worked examples based on pragmatic test accuracy study data are used in chapters to illustrate relevance to day-to-day clinical practice. Readers will gain an understanding of sensitivity and specificity and predictive values along with many other parameters. The contents are highly structured, and the use of worked examples facilitates understanding and interpretation. This book is a resource for clinicians in any discipline who are involved in the performance or assessment of test accuracy studies and professionals in the disciplines of machine learning or informatics wishing to gain insight into clinical applications of 2x2 tables. 0aBiometry.965981 0aNeurology .966816 0aMedical informatics.960693 0aMachine learning.95505914aBiostatistics.96598524aNeurology.96681624aHealth Informatics.24aMachine Learning.9550592 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303147193308iPrinted edition:z978303147195740uhttps://doi.org/10.1007/978-3-031-47194-0  aZDB-2-SME  aZDB-2-SXM  c57121d57121