03729nam a22006255i 4500 978-981-97-7451-7 DE-He213 20251030113234.0 cr nn 008mamaa 241018s2024 si | s |||| 0|eng d 9789819774517 978-981-97-7451-7 10.1007/978-981-97-7451-7 doi R1 MFKC bicssc MED082000 bisacsh MFKC thema Data-Driven Reproductive Health [electronic resource] : Role of Bioinformatics and Machine Learning Methods / edited by Abhishek Sengupta, Priyanka Narad, Gaurav Majumdar, Deepak Modi. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. XI, 231 p. 25 illus., 23 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda 1 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. This 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. Reproductive health. 58885 Gynecology . 64086 Midwifery. Bioinformatics. 64050 Computational intelligence. 64052 Artificial intelligence. 58441 Reproductive Medicine. 69390 Gynecology. 64086 Midwifery. Bioinformatics. 64050 Computational Intelligence. 64052 Artificial Intelligence. 58441 Sengupta, Abhishek. editor. edt http://id.loc.gov/vocabulary/relators/edt 86238 Narad, Priyanka. editor. edt http://id.loc.gov/vocabulary/relators/edt 86239 Majumdar, Gaurav. editor. edt http://id.loc.gov/vocabulary/relators/edt 86095 Modi, Deepak. editor. edt http://id.loc.gov/vocabulary/relators/edt 86240 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819774500 Printed edition: 9789819774524 Printed edition: 9789819774531 https://doi.org/10.1007/978-981-97-7451-7 ZDB-2-SME ZDB-2-SXM 64305 64305