| ORIGINAL ARTICLE |
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| Year : 2020 | Volume
: 8
| Issue : 2 | Page : 107-112 |
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Statistical corner: Using R to build, analyse and plot clinical neurological datasets
Mikko Jaakko Pyysalo1, Teemu Vesterinen2
1 City of Tampere, Oral Health Services; Oral and Maxillofacial Unit, Tampere University Hospital; Hemorrhagic, Brain Pathology Research Group, University of Tampere, Tampere, Finland
2 Hemorrhagic, Brain Pathology Research Group, University of Tampere; Vestigo Data Mining, Development Engineer, Tampere, Finland
Correspondence Address:
Dr. Mikko Jaakko Pyysalo
City of Tampere, Oral Health Services; Oral and Maxillofacial Unit, Tampere University Hospital; Hemorrhagic, Brain Pathology Research Group, University of Tampere, Tampere
Finland
 Source of Support: None, Conflict of Interest: None
DOI: 10.4103/jcvs.jcvs_29_20
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Introduction: In the field of medical research, large volumes of data need to be analysed accurately, and it is crucial to pre-process the data before it can be analysed. The 'R' environment is a programming language and environment for statistical computing and graphics suitable for the analysis of data sets.
Objectives: To provide examples on how to utilise the R language for data processing, and its usefulness for medical researchers.
Materials and Methods: Two real world datasets, ie, data for: 'Effect of Morning Blood Pressure Peak on Early Progressive Ischemic Stroke: A Prospective Clinical Study' and data for: 'Impact of early surgery of ruptured cerebral aneurysms on vasospasm and hydrocephalus after SAH: our preliminary series' have been used to present an example for two different approaches for the process of data analysis using R.
Results: Accurate and tidy data sets were obtained.
Conclusions: R is a reliable environment for the processing of large data sets.
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