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Artificial Intelligence-Based Medical Data Mining
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OA
AI
DOI：10.3390/jpm12091359.png)
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摘要
En 中文
Understanding published unstructured textual data using traditional text mining approaches and tools is becoming a challenging issue due to the rapid increase in electronic open-source publications. The application of data mining techniques in the medical sciences is an emerging trend; however, traditional text-mining approaches are insufficient to cope with the current upsurge in the volume of published data. Therefore, artificial intelligence-based text mining tools are being developed and used to process large volumes of data and to explore the hidden features and correlations in the data. This review provides a clear-cut and insightful understanding of how artificial intelligence-based data-mining technology is being used to analyze medical data. We also describe a standard process of data mining based on CRISP-DM (Cross-Industry Standard Process for Data Mining) and the most common tools/libraries available for each step of medical data mining.
Keyword:
text mining
artificial intelligence
machine learning
medical data
healthcare information
期刊
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3
论文数:
7.5K
被引数:
1.6W
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