Health Analytics with R

Health Analytics with R

Learning Data Science Using Examples from Healthcare and Direct-to-Consumer Genetics

Boland, Mary Regina

Springer International Publishing AG

01/2025

660

Dura

9783031743825

15 a 20 dias

Descrição não disponível.

Chapter 1-Introduction.- Chapter 2-Genetics Analysis for Health Analytics.- Chapter 3-Determining Phenotypic Traits from Single Nucleotide Polymorphism (SNP) Data.- Chapter 4-Clinical Genetic Databases: ClinVar, ACMG Clinical Practice Guidelines.- Chapter 5-Inferring Disease Risk from Genetics.- Chapter 6-Challenges in Health Analytics Due to Lack of Diversity in Genetic Research: Implications and Issues with Published Knowledge.- Chapter 7-Clinical Data and Health Data Types.- Chapter 8-Clinical Datasets: Open Access Electronic Health Records Datasets.- Chapter 9-Association Mining with Clinical Data: Phenotype-Wide Association Studies (PheWAS).- Chapter 10-Organizing a Clinical Study Across Multiple Clinical Systems: Common Data Models.- Chapter 11-Environmental Health Data Types for Health Analytics.- Chapter 12-Geospatial Analysis Using Environmental Health Data.- Chapter 13-Social Determinants of Health Data for Health Analytics.- Chapter 14-Geospatial Analysis Using Social Determinants of Health, Clinical Data and Spatial Regression Methods.- Chapter 15-Ethics.

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R;directtoconsumer;data science;data analytics;genetics;health analytics;Direct-to-consumer genetics;R code;data mining;clinical data;precision medicine;personalized medicine;Direct-to-consumer genetics