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008			230118b ||||| |||| 00| 0 eng d
020			_a9780367428198
082			_a610.2855133 _bHAR
100			_aHarrison, Ewen _910531
245			_aR for health data science
260			_bCRC Press _aBoco Raton _c2021
300			_axix, 343
365			_aGBP _b42.99
504			_aTable of Contents I Data wrangling and visualisation 1. Why we love R 2 R basics 3 Summarising data 4 Different types of plots 5 Fine tuning plots II Data analysis 6 Working with continuous outcome variables 7 Linear regression 8 Working with categorical outcome variables 9 Logistic regression 10 Time-to-event data and survival III Workflow 11 The problem of missing data 12 Notebooks and Markdown 13 Exporting and reporting 14 Version control 15 Encryption
520			_aIn this age of information, the manipulation, analysis, and interpretation of data have become a fundamental part of professional life; nowhere more so than in the delivery of healthcare. From the understanding of disease and the development of new treatments, to the diagnosis and management of individual patients, the use of data and technology is now an integral part of the business of healthcare. Those working in healthcare interact daily with data, often without realising it. The conversion of this avalanche of information to useful knowledge is essential for high-quality patient care. R for Health Data Science includes everything a healthcare professional needs to go from R novice to R guru. By the end of this book, you will be taking a sophisticated approach to health data science with beautiful visualisations, elegant tables, and nuanced analyses.
650			_aMedical informatics _97680
650			_aR (Computer program language) _91512
650			_aBioinformatics _911374
700			_aPius, Riinu _911375
942			_2ddc _cBK