Introduction
Recent years have witnessed a tremendous increase in the use of machine learning for biomedical applications. This surge in interest has several causes. One is the successful application of machine learning technologies in other fields such as web search, speech and handwriting recognition, agent design, spatial modeling, etc. Another is the development of technologies that enable the production of large amounts of data in the time it used to take to generate a single data point (run a single experiment). A third most recent development is the advent of Electronic Medical/Health Records (EMRs/EHRs). The drastic increase in the amount of data generated has led the biologists and clinical researchers to adopt algorithms that can construct predictive models from large amounts of data. Naturally, machine learning is emerging as a tool of choice.
In this article, we will present a few data types and tasks involving such large-scale biological data, where machine learning...
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Page, C.D., Natarajan, S. (2011). Biomedical Informatics. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_81
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DOI: https://doi.org/10.1007/978-0-387-30164-8_81
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