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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 ...
BioData Mining is a peer-reviewed open access scientific journal covering data mining methods applied to computational biology and medicine established in 2008. It is published by BioMed Central and the editors-in-chief are Jason H. Moore and Marylyn D. Ritchie ( University of Pennsylvania ).
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 ...
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.
This data mining method has been explored in different fields including disease diagnosis, market basket analysis, retail industry, higher education, and financial analysis. In retail, affinity analysis is used to perform market basket analysis, in which retailers seek to understand the purchase behavior of customers.
Machine learning techniques such as deep learning can learn features of data sets rather than requiring the programmer to define them individually. The algorithm can further learn how to combine low-level features into more abstract features, and so on. This multi-layered approach allows such systems to make sophisticated predictions when ...
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.
These models demonstrate the significant potential of PubMed data in enhancing the capabilities of AI in medical research and healthcare applications. Such advancements underline the growing intersection between large-scale data mining and AI development in the biomedical field.