Browse > Article

DNA Inspired CVD Diagnostic Hardware Architecture  

Kwon, Oh-Hyuk (인하대 공대 정보통신공학과)
Kim, Joo-Kyung (서울대 공대 컴퓨터공학부)
Ha, Jung-Woo (서울대 공대 컴퓨터공학부)
Park, Jea-Hyun (인하대 공대 정보통신공학과)
Chung, Duck-Jin (인하대 공대 정보통신공학과)
Lee, Chong-Ho (인하대 공대 정보통신공학과)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.57, no.2, 2008 , pp. 320-326 More about this Journal
Abstract
In this paper, we propose a new algorithm emulating the DNA characteristics for noise-tolerant pattern matching problem on digital system. The digital pattern matching becomes core technology in various fields, such as, robot vision, remote sensing, character recognition, and medical diagnosis in particular. As the properties of natural DNA strands allow hybridization with a certain portion of incompatible base pairs, DNA-inspired data structure and computation technique can be adopted to bio-signal pattern classification problems which often contain imprecise data patterns. The key feature of noise-tolerance of DNA computing comes from control of reaction temperature. Our hardware system mimics such property to diagnose cardiovascular disease and results superior classification performance over existing supervised learning pattern matching algorithms. The hardware design employing parallel architecture is also very efficient in time and area.
Keywords
CVD diagnosis; Pattern matching; Noise tolerance; DNA computing;
Citations & Related Records

Times Cited By SCOPUS : 0
연도 인용수 순위
  • Reference
1 Watada J., Kojima S., Ueda S., Ono O., "DNA Computing Approach to Optimal Decision Problems", International Journal of Innovative Computing Information and Control, vol. 2, no. 1, pp. 273-282, 2006
2 S. Surzycki,, Basic Techniques in Molecular Biology, Springer Lab Manual, Germany, 2000
3 엄재홍, 김병희, 이제근, 허민오, 박영진, 김민혁, 김성천, 장병탁, "AptaCDSS - 압타머칩을 이용한 심혈관 질환 질환단계 예측 및 진단의사결정지원 시스템", 한국정보과학회 가을 학술발표논문집, vol. 33, no. 2, pp. 28-32, 2006
4 L. Adleman, "Molecular computation of solutions to combinatorial problems", Science, vol. 266, no. 5187, pp. 1021-1024, 1994   DOI
5 WHO Fact sheet N.317, http://www.who.int/-mediacentre/factsheets/fs317/en/index.html
6 Jayasena, S.D., "Aptamers: an emerging class of molecules that rival antibodies in diagnostics", Clinical Chemistry, 45(9), pp. 1628-1650, 1999
7 신세현, "심혈관 질환 조기진단을 위한 미세유체역학 과 광학기술의 융합", Optical Society of Korea Annual Meeting 2005, pp. 24-25, 2005
8 Liwen. D. I., "DNA computing", Computing in Science & Engineering, vol. 4, no. 3, pp. 5-8, 2002
9 J. -W. Ha, J. -H. Eom, S. -C. Kim, and B. -T. Zhang, "Evolutionary hypernetwork models for aptamer-based cardiovascular disease diagnosis", The Genetic and Evolutionary Computation Conference, Vol. 4, 2007
10 L. Adleman, "Computing with DNA", Sci. Amer., vol. 279, no. 2, pp. 54-62, 1998
11 University of Waikato New Zealand, "Waikato Environment for Knowledge Analysis (Weka)", http://www.cs.waikato.ac.nz/ml/weka/index.html
12 WHO Programmer and projects, "Cardiovascular diseases", http://www.who.int/cardiovasculardiseases/en/?s=0009
13 Tsaftaris S. A., Katsaggelos A. K., Pappas T. N., Papoutsakis E. T., "DNA-Based Matching of Digital Signals", Acoustics, Speech, and Signal Processing, vol. 5, pp. V-581-584, 2004
14 D. E. Knuth, The Art of Computer Programming, Addison-Wesley Publishing Company, 1982, vol. 2