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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.
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 ...
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 ...
From a historical viewpoint, medical informatics scientists (also known as medical informaticians) started to use artificial intelligence and Bayesian statistical methods in diagnosis and medical decision making, as early as in the 1970s. An example is the MYCIN system developed at Stanford University. The field has since evolved to use a wide ...
An example of a text mining protocol used in a study of protein-protein complexes, or protein docking [91] Text mining applications in the biomedical field include computational approaches to assist with studies in protein docking , [ 91 ] protein interactions , [ 92 ] [ 93 ] and protein-disease associations. [ 94 ]
The related terms data dredging, data fishing, and data snooping refer to the use of data mining methods to sample parts of a larger population data set that are (or may be) too small for reliable statistical inferences to be made about the validity of any patterns discovered. These methods can, however, be used in creating new hypotheses to ...
gretl is an example of an open-source statistical package. ADaMSoft – a generalized statistical software with data mining algorithms and methods for data management; ADMB – a software suite for non-linear statistical modeling based on C++ which uses automatic differentiation; Chronux – for neurobiological time series data; DAP – free ...
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]