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001 9781003185598
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006 m o d
007 cr |||||||||||
008 220722s2023 flu ob 001 0 eng
040 _aOCoLC-P
_beng
_erda
_cOCoLC-P
020 _a9781003185598
_q(ebook)
020 _a1003185592
020 _a9781000823691
_q(electronic bk. : PDF)
020 _a1000823695
_q(electronic bk. : PDF)
020 _a9781000823714
_q(electronic bk. : EPUB)
020 _a1000823717
_q(electronic bk. : EPUB)
020 _z9781032028767
_q(hardback)
020 _z9781032028774
_q(paperback)
024 7 _a10.1201/9781003185598
_2doi
035 _a(OCoLC)1350913981
035 _a(OCoLC-P)1350913981
050 0 0 _aRC263
072 7 _aMAT
_x029010
_2bisacsh
072 7 _aPBT
_2bicssc
082 0 0 _a616.99/4
_223/eng/20221115
100 1 _aBhattacharjee, Atanu,
_eauthor.
245 1 0 _aBig data analytics in oncology with R /
_cAtanu Bhattacharjee.
250 _aFirst edition.
264 1 _aBoca Raton :
_bChapman & Hall/CRC Press,
_c2023.
300 _a1 online resource
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
520 _a"Big Data Analytics in Oncology with R serves the analytical approaches for big data analysis. There is huge progressed in advanced computation with R. But there are several technical challenges faced to work with big data. These challenges are with computational aspect and work with fastest way to get computational results. Clinical decision through genomic information and survival outcomes are now unavoidable in cutting-edge oncology research. This book is intended to provide a comprehensive text to work with some recent development in the area"--
_cProvided by publisher.
588 _aOCLC-licensed vendor bibliographic record.
650 0 _aBig data.
650 0 _aOncology
_xData processing.
650 0 _aR (Computer program language)
650 7 _aMATHEMATICS / Probability & Statistics / Bayesian Analysis
_2bisacsh
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9781003185598
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999 _c4990
_d4990