Abstract
A prediction model that exploits the past medical patient history to determine the risk of individuals to develop future diseases is proposed. The model is generated by using the set of frequent diseases that contemporarily appear in the same patient. The illnesses a patient could likely be affected in the future are obtained by considering the items induced by high confidence rules generated by the frequent diseases. Furthermore, a phenotypic comorbidity network is built and its structural properties are studied in order to better understand the connections between illnesses. Experimental results show that the proposed approach is a promising way for assessing disease risk.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Albert, R., Barabási, A.-L.: Staistical mechanics of complex networks. Reviews of modern physics 74, 47–97 (2002)
Davis, D.A., Chawla, N.V., Christakis, N.A., Barabási, A.-L.: Time to CARE: a collaborative engine for practical disease prediction. Data Mining and Knowledge Discovery Journal 20, 388–415 (2010)
Hidalgo, C.A., Blumm, N., Barabási, A.-L., Christakis, N.A.: A dynamic network approach for the study of human phenotypes. PLoS Computational Biology 5(4) (2009)
Steinhaeuser, K., Chawla, N.V.: A network-based approach to understanding and predicting diseases. In: Social Computing and Behavioral Modeling. Springer, Heidelberg (2009)
Tan, P.-N., Steinbach, M., Kumar, V.: Introduction to Data Mining. Pearson International Edition, London (2006)
Wasserman, S., Faust, K.: Social Network Analysis. Methods and Applications. Cambridge University Press, Cambridge (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Folino, F., Pizzuti, C., Ventura, M. (2010). A Comorbidity Network Approach to Predict Disease Risk. In: Khuri, S., Lhotská, L., Pisanti, N. (eds) Information Technology in Bio- and Medical Informatics, ITBAM 2010. ITBAM 2010. Lecture Notes in Computer Science, vol 6266. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15020-3_10
Download citation
DOI: https://doi.org/10.1007/978-3-642-15020-3_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15019-7
Online ISBN: 978-3-642-15020-3
eBook Packages: Computer ScienceComputer Science (R0)