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  2. Data mining - Wikipedia

    en.wikipedia.org/wiki/Data_mining

    There have been some efforts to define standards for the data mining process, for example, the 1999 European Cross Industry Standard Process for Data Mining (CRISP-DM 1.0) and the 2004 Java Data Mining standard (JDM 1.0). Development on successors to these processes (CRISP-DM 2.0 and JDM 2.0) was active in 2006 but has stalled since.

  3. KNIME - Wikipedia

    en.wikipedia.org/wiki/KNIME

    KNIME (/ n aɪ m / ⓘ), the Konstanz Information Miner, [2] is a free and open-source data analytics, reporting and integration platform.KNIME integrates various components for machine learning and data mining through its modular data pipelining "Building Blocks of Analytics" concept.

  4. Biomedical data science - Wikipedia

    en.wikipedia.org/wiki/Biomedical_data_science

    Biomedical data science is a multidisciplinary field which leverages large volumes of data to promote biomedical innovation and discovery. Biomedical data science draws from various fields including Biostatistics , Biomedical informatics , and machine learning , with the goal of understanding biological and medical data.

  5. Cross-industry standard process for data mining - Wikipedia

    en.wikipedia.org/wiki/Cross-industry_standard...

    The outer circle in the diagram symbolizes the cyclic nature of data mining itself. A data mining process continues after a solution has been deployed. The lessons learned during the process can trigger new, often more focused business questions, and subsequent data mining processes will benefit from the experiences of previous ones.

  6. Health care analytics - Wikipedia

    en.wikipedia.org/wiki/Health_care_analytics

    Health care analytics is the health care analysis activities that can be undertaken as a result of data collected from four areas within healthcare: (1) claims and cost data, (2) pharmaceutical and research and development (R&D) data, (3) clinical data (such as collected from electronic medical records (EHRs)), and (4) patient behaviors and preferences data (e.g. patient satisfaction or retail ...

  7. Affinity analysis - Wikipedia

    en.wikipedia.org/wiki/Affinity_analysis

    Considering all the above-mentioned definitions, affinity analysis can develop rules that will predict the occurrence of an event based on the occurrence of other events. This data mining method has been explored in different fields including disease diagnosis, market basket analysis, retail industry, higher education, and financial analysis.

  8. Clinical data repository - Wikipedia

    en.wikipedia.org/wiki/Clinical_data_repository

    The use of Clinical Data Repositories could provide a wealth of knowledge about patients, their medical conditions, and their outcome. The database could serve as a way to study the relationship and potential patterns between disease progression and management. The term "Medical Data Mining" has been coined for this method of research.

  9. Biomedical text mining - Wikipedia

    en.wikipedia.org/wiki/Biomedical_text_mining

    Biomedical text mining (including biomedical natural language processing or BioNLP) refers to the methods and study of how text mining may be applied to texts and literature of the biomedical domain. As a field of research, biomedical text mining incorporates ideas from natural language processing , bioinformatics , medical informatics and ...