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020 _a9789819774517
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024 7 _a10.1007/978-981-97-7451-7
_2doi
050 4 _aR1
072 7 _aMFKC
_2bicssc
072 7 _aMED082000
_2bisacsh
072 7 _aMFKC
_2thema
245 1 0 _aData-Driven Reproductive Health
_h[electronic resource] :
_bRole of Bioinformatics and Machine Learning Methods /
_cedited by Abhishek Sengupta, Priyanka Narad, Gaurav Majumdar, Deepak Modi.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXI, 231 p. 25 illus., 23 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _a1 Introduction to Data Mining in Reproductive Health -- 2 Reproductive Health Data Sources -- 3 Pre-processing and Integration of Reproductive Health Data -- 4 Multi-omics Approaches for Reproductive Health Data -- 5 Association Rule Mining in Reproductive Health Data -- 6 Modeling in Reproductive Health and Treatment Outcomes -- 7 Clustering Analysis of Reproductive Health Data -- 8 Text Mining and NLP in Reproductive Health -- 9 Time Series Analysis in Reproductive Health Data -- 10 Data Mining Ethics in Reproductive Health -- 11 Reproductive Health Data Mining: Case Studies -- 12 Future Directions and Emerging Trends in Reproductive Health.
520 _aThis book provides insight into the transformative impact of data-driven approaches on reproductive health. Chapters cover a wealth of intricate algorithms of genomic analysis, predictive modeling, and personalized treatment strategies, providing an up-to-date view of the reproductive healthcare landscape. With more than 20 code-based examples, the book decodes complex biological data using bioinformatics and machine learning and provides valuable insights into fertility, genetic disorders, and personalized medicine. This book is relevant for healthcare professionals, researchers, and students in the fields of reproductive medicine, bioinformatics, and genetics.
650 0 _aReproductive health.
_958885
650 0 _aGynecology .
_964086
650 0 _aMidwifery.
650 0 _aBioinformatics.
_964050
650 0 _aComputational intelligence.
_964052
650 0 _aArtificial intelligence.
_958441
650 1 4 _aReproductive Medicine.
_969390
650 2 4 _aGynecology.
_964086
650 2 4 _aMidwifery.
650 2 4 _aBioinformatics.
_964050
650 2 4 _aComputational Intelligence.
_964052
650 2 4 _aArtificial Intelligence.
_958441
700 1 _aSengupta, Abhishek.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_986238
700 1 _aNarad, Priyanka.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_986239
700 1 _aMajumdar, Gaurav.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_986095
700 1 _aModi, Deepak.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_986240
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789819774500
776 0 8 _iPrinted edition:
_z9789819774524
776 0 8 _iPrinted edition:
_z9789819774531
856 4 0 _uhttps://doi.org/10.1007/978-981-97-7451-7
912 _aZDB-2-SME
912 _aZDB-2-SXM
999 _c64305
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