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Chapter 4: Semantic analytics of biomedical data

    A part of this chapter is revised from Charles C. N. Wang, Phillip C.-Y. Sheu, and Jeffrey J. P. Tsai, Towards Semantic Biomedical Problem Solving, Int. J. Semantic Computing, Vol 09, pp 415 (2015).

    https://doi.org/10.1142/9789813207981_0004Cited by:0 (Source: Crossref)
    Abstract:

    Biomedical intelligence (BMI) has been studied in solos, lacking a systematic methodology. Bioinformatics has been conceptualizing biological process in terms of genomics and applying computer science (derived from disciplines such as applied modeling, data mining, machine learning and statistics) to extract knowledge from biological data. Medical Informatics, on the other hand, has been developing health care applications based on clinical observations and applying computer science to extract knowledge and information to facilitate problem solving and decision marking In this chapter, we describe how semantic computing can enhance biological and medical intelligence. Specifically, we show how structured natural language (SNL) can express many problems in BMI with a finite number of sentence patterns, and show how biological analysis tools, OLAP, data mining and statistical analysis may be linked to solve problems related to biomedical data.