Top data mining tools for the healthcare industry
| Autor: | Jorge Bernardino, Judith Santos-Pereira, Le Gruenwald |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
Complex data type
General Computer Science Computer science business.industry Healthcare Open-source data mining tools 020206 networking & telecommunications 02 engineering and technology computer.software_genre Health care Spark (mathematics) 0202 electrical engineering electronic engineering information engineering Healthcare industry 020201 artificial intelligence & image processing Data mining Healthcare data business computer Selection (genetic algorithm) |
| Zdroj: | Journal of King Saud University - Computer and Information Sciences. 34:4968-4982 |
| ISSN: | 1319-1578 |
| Popis: | The healthcare industry has become increasingly challenging, requiring retrieval of knowledge from large amounts of complex data to find the best treatments. Several works have suggested the use of Data Mining tools to overcome the challenges; however, none of them has suggested the best tool to do so. To fill this gap, this paper presents a survey of popular open-source data mining tools in which data mining tool selection criteria based on healthcare application requirements is proposed and the best ones using the proposed selection criteria are identified. The following popular open-source data mining tools are assessed: KNIME, R, RapidMiner, Scikit-learn, and Spark. The study shows that KNIME and RapidMiner provide the largest coverage of healthcare data mining requirements. |
| Databáze: | OpenAIRE |
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