Evaluation of machine learning techniques for classification of kidney biopsy report sections assisted by DeCS terminology
Abstract
Natural language processing is nowadays a valuable resource in biomedical informatics mainly due to the increasing demand for knowledge and the availability of documents in digital format. This paper describes the use and evaluation of five machine learning techniques applied to renal biopsy reports written as free text. The pre-processing and the named entity recognition tasks using the DeCS terminology is also reported.
References
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Bodenreider, O. The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic Acids Research, 32(suppl.1):D267–D270, January 2004.
Rink B, Harabagiu S, Roberts K., Automatic extraction of relations between medical concepts in clinical texts, J Am Med Inform Assoc. 2011 Sep-Oct;18(5):594-600.
Jiang M, Chen Y, Liu M, Rosenbloom ST, Mani S, Denny JC, Xu H., A study of machine-learning-based approaches to extract clinical entities and their assertions from discharge summaries, J Am Med Inform Assoc. 2011 Sep-Oct;18(5):601-6.
Patrick JD, Nguyen DH, Wang Y, Li M., A knowledge discovery and reuse pipeline for information extraction in clinical notes, J Am Med Inform Assoc. 2011 Sep-Oct;18(5):574-9.
Patel CO, Cimino JJ, Using semantic and structural properties of the Unified Medical Language System to discover potential terminological relationships, J Am Med Inform Assoc. 2009 May-Jun;16(3):346-53.
Porter MF. An algorithm for suffix stripping. Program: electronic library & information systems. 2006;40(3):211-218. DOI: 10.1108/00330330610681286.
Weiss SM, Indurkhya N, Predictive Data Mining: A Practical Guide, MK, San Francisco, CA, 1998.
Witten I. H, Frank E. Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. San Francisco, 1999
Published
2012-07-16
How to Cite
NICOLAS, Flávia P.; ABRAHAM, K. J.; REIS, Amanda R.; PISA, Ivan T.; RUIZ, Evandro E. S..
Evaluation of machine learning techniques for classification of kidney biopsy report sections assisted by DeCS terminology. In: BRAZILIAN SYMPOSIUM ON COMPUTING APPLIED TO HEALTH (SBCAS), 12. , 2012, Curitiba/PR.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2012
.
p. 208-211.
ISSN 2763-8952.
