Name
Title | ||
|---|---|---|
Modelling and extraction of variability in free-text medication prescriptions from an anonymised primary care electronic medical record research database. |
Abstract | ||
|---|---|---|
BackgroundFree-text medication prescriptions contain detailed instruction information that is key when preparing drug data for analysis. The objective of this study was to develop a novel model and automated text-mining method to extract detailed structured medication information from free-text prescriptions and explore their variability (e.g. optional dosages) in primary care research databases. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1186/s12911-016-0255-x | BMC Med. Inf. & Decision Making |
Keywords | Field | DocType |
Text mining, Natural language processing, Dose information, Prescriptions, CPRD | Primary health care,Data mining,Electronic prescribing,Data anonymization,Primary care,Medical record,Health informatics,Medicine,Database,Medical prescription | Journal |
Volume | Issue | ISSN |
16 | 1 | 1472-6947 |
Citations | PageRank | References |
2 | 0.37 | 14 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| George Karystianis | 1 | 22 | 2.15 |
| Therese Sheppard | 2 | 2 | 0.37 |
| William G. Dixon | 3 | 11 | 2.42 |
| Goran Nenadic | 4 | 228 | 13.18 |