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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.
Databases for oncogenomic research are biological databases dedicated to cancer data and oncogenomic research. They can be a primary source of cancer data, offer a certain level of analysis (processed data) or even offer online data mining .
In collaboration with the university and regional library in Münster, all gathered files are archived and allocated to every German library, securing a sustainable use of this meta-data-repository. The medical-data-portal is known as German (RIsources) and European research infrastructure (MERIL) and is developed by the Institute of Medical ...
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.
An example of data mining related to an integrated-circuit (IC) production line is described in the paper "Mining IC Test Data to Optimize VLSI Testing." [12] In this paper, the application of data mining and decision analysis to the problem of die-level functional testing is described. Experiments mentioned demonstrate the ability to apply a ...
The primary goal of bioinformatics is to increase the understanding of biological processes. What sets it apart from other approaches is its focus on developing and applying computationally intensive techniques to achieve this goal. Examples include: pattern recognition, data mining, machine learning algorithms, and visualization.
The advent of social media has recently led to new online research methods, for example data mining of large datasets from such media [6] or web-based experiments within social media that are entirely under the control of researchers, e.g. those created with the software Social Lab. [7]
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.