Using Data Mining Strategies in Clinical Decision Making: A Literature Review
| Autor: | Lu Yen A. Chen, Tonks N Fawcett |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Organizational Behavior and Human Resource Management
Nursing (miscellaneous) Knowledge management 020205 medical informatics Computer science Strategy and Management Clinical Decision-Making MEDLINE Pharmaceutical Science Health Informatics 02 engineering and technology computer.software_genre Health informatics 03 medical and health sciences Patient safety Multiple Models Clinical decision making Drug Discovery 0202 electrical engineering electronic engineering information engineering Nursing Informatics Data Mining Humans Marketing Pharmacology 030504 nursing business.industry Principal (computer security) Models Theoretical Data mining 0305 other medical science business computer |
| Zdroj: | Computers, informatics, nursing : CIN. 34(10) |
| ISSN: | 1538-9774 |
| Popis: | Several data-mining models have been embedded in the clinical environment to improve decision making and patient safety. Consequently, it is crucial to survey the principal data-mining strategies currently used in clinical decision making and to determine the disadvantages and advantages of using these strategies in data mining in clinical decision making. A literature review was conducted, which identified 21 relevant articles. The article findings showed that multiple models of data mining were used in clinical decision making. Although data mining is efficient and accurate, the models are limited with respect to disease and condition. |
| Databáze: | OpenAIRE |
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