A Grid-based HIV expert system

被引：19
作者：
Sloot P.M.A. [1 ]
Boukhanovsky A.V. [2 ]
Keulen W. [3 ]
Tirado-Ramos A. [1 ]
Boucher C.A. [4 ]
机构：
[1] Section Computational Science, University of Amsterdam, 1098 SJ Amsterdam
[2] Institute for High Performance Computing and Information Systems, St. Petersburg
[3] Department of Virology Education
[4] University of Utrecht
来源：
Journal of Clinical Monitoring and Computing | 2005年 / 19卷 / 4-5期
关键词：
Artificial intelligence; Bio-statistics; Computational Grids; Expert system; HIV; PSE;
D O I：
10.1007/s10877-005-0673-2
中图分类号：
学科分类号：
摘要：
Objectives. This paper a ddresses Grid-based integration and access of distributed data from infectious disease patient databases, literature on in-vitro and in-vivo pharmaceutical data, mutation databases, clinical trials, simulations and medical expert knowledge. Methods. Multivariate analyses combined with rule-based fuzzy logic are applied to the integrated data to provide ranking of patient-specific drugs. In addition, cellular automata-based simulations are used to predict the drug behaviour over time. Access to and integration of data is done through existing Internet servers and emerging Grid-based frameworks like Globus. Data presentation is done by standalone PC based software, Web-access and PDA roaming WAP access. The experiments were carried out on the DAS2, a Dutch Grid testbed. Results. The output of the problem-solving environment (PSE) consists of a prediction of the drug sensitivity of the virus, generated by comparing the viral genotype to a relational database which contains a large number of phenotype-genotype pairs. Conclusions. Artificial Intelligence and Grid technology are effectively used to abstract knowledge from the data and provide the physicians with adaptive interactive advice on treatment applied to drug resistant HIV. An important aspect of our research is to use a variety of statistical and numerical methods to identify relationships between HIV genetic sequences and antiviral resi stance to investigate consistency of results. © Springer Science + Business Media, Inc. 2005.
引用
收藏
页码：263 / 278
页数：15
相关论文
共 12 条
[1]  
Zhao Z., Belleman R.G., van Albada G.D., Sloot P.M.A., AG-IVE: An Agent-Based Solution to Constructing Interactive Simulation Systems, Series Lecture Notes in Computer Science, 2329, pp. 693-703, (2002)
[2]  
Durant J., Clevenbergh P., Halfon P., Delguidice P., Porsin S., Simonet P., Montagne N., Dohin E., Schapiro J.M., Boucher C., Dellamonica P., Improving HIV therapy with drug resistance genotyping: The Viradapt Study, Lancet, 353, pp. 2195-2199, (1999)
[3]  
Sevin A.D., DeGruttola, Nijhuis M., Schapiro J.M., Foulkes A.S., Para M.F., Boucher C.A.B., Methods for Investigation of the Relationship between Drug-Susceptibility Phenotype and Human Immunodeficiency Virus Type 1 Genotype with Applications to AIDS Clinical Trials Groupw 333, The Journal of Infectious Diseases, 182, pp. 59-67, (2000)
[4]  
The Genotype database is obtained from a large service testing laboratory from the US. It contains the resistance profiles of the Protease and Reverse Transcriptase genes of the HIV-1 virus obtained from plasma samples of HIV-1 infected patients
[5]  
Mathematical Methods for DNA Sequences, (1999)
[6]  
Kiryukhin I., Saskov K., Boukhanovsky A.V., Keulen W., Boucher C.A., Sloot P.M.A., Stochastic modeling of temporal variability of HIV-1 population, Proceedings Part I, in Series Lecture Notes in Computer Science, 2657, pp. 125-135, (2003)
[7]  
Zorzenon dos Santos R.M., Coutinho S., Dynamics of HIV infection: A cellular automata approach, Phys Rev Lett, 87, 16, (2001)
[8]  
Sloot P.M.A., Chen F., Boucher C.A., Cellular automata model of drug therapy for HIV infection, 5th International Conference on Cellular Automata for Research and Industry, 2493, pp. 282-293, (2002)
[9]  
Alimadhi F., Mobile Internet: Wireless access to Web-based interfaces of legacy simulations, (2002)
[10]  
Little S.J., Holte S., Routy J.P., Daar E.S., Markowitz M., Collier A.C., Koup R.A., Mellors J.W., Connick E., Conway B., Kilby M., Wang L., Whitcomb J.M., Hellmann N.S., Richman D.D., Antiretroviral-drug resistance among patients recently infected with HIV, N Engl J Med, 8, 6, pp. 385-394, (2002)
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