Titlebook: Data-Driven Reproductive Health; Role of Bioinformati Abhishek Sengupta,Priyanka Narad,Deepak Modi Book 2024 The Editor(s) (if applicable)

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978-981-97-7453-1The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor

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Introducing the Winning Scientific Formulah on reproductive health has been at the forefront of healthcare research due to awareness and a plethora of studies generated on the same. This chapter serves as an introduction to the process of data mining in reproductive health covering the basic methodology and applications of data mining in re

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Defects in Crystals and Plastic Deformation,ter delves into exploring the role of genetics in reproductive problems and investigates the gene expression dynamics in reproductive development and biomarker prediction through proteomics analysis. The chapter also focuses on each of these technologies and their applications individually to the fi

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lysis, help understand these complexities. This chapter discusses the different clustering algorithms that can be used on reproductive health data such as k-means, hierarchical, density-based clustering (e.g., DBSCAN), and model-based clustering (e.g., Gaussian mixture models). Furthermore, the chap