Fuzzy-Neuropsychiatric Predictive Model

  • Frank Amadin UNIVERSITY OF BENIN
  • Obi J.C.
Keywords: Fuzzy Logic, Neural Network, Psychiatric, UML

Abstract

Due to subjective diagnosis approach, psychiatric diagnosis, prognosis and predication has been tremendously difficult. In short, it has been subjective; tied to a particular human expert with overview on psychiatric diagnosis. Overtimes, inadequate, ineffective and exhaustive medical professional has contributed seriously to poor psychiatric diagnosis. Artificial Intelligence (AI) has shown rich potential in this area. Therefore this research paper has predictively proposed a fuzzy–neural model capable of imprecision or vague handling in collaboration with system self-learning or training using fuzzy logic and neural, subdomain of Soft-Computing (SC) and Artificial intelligence. The various views of the model were visualized using Unified Modeling Language (UML) while system implementation was opened to future research.

Author Biography

Frank Amadin, UNIVERSITY OF BENIN

Computer Sciece,

Senior Lecturer

References

Adyles A. J., Fabrício C. L. A. (2010), “Automatic Faults Diagnosis by Application of Neural Network System and Condition-based Monitoring Using Vibration Signals, retrieved from http://www.informatics.org.cn/doc/ucit201001/ucit20100104.pdf

Angel C. and Rocio R. ( 2011), “Documentation management with Ant colony Optimization Metaheuristic: A Fuzzy Text Clustering Approach Using Pheromone trails” retrieved from soft computing in Industrial applications, Advances in intelligient and soft Computing, 2011 vol. 96, 2011, 261-70, DOI: 10.1007/978-3-642-20505-1_23

Christos S. and Dimitros S. (2008), “Neural Network” retrieved from http//:docs.toc.com/doc/1505/neural-networks.

Dase R.K. and Pawar D.D. (2010), “Application of Neural network to stock market prediction: A review of literature”, retrieved from http://www.bioinfo.in/uploadfiles/12843

FMOH (2004), Revised National Health Policy, Federal Ministry of Health, Abuja

Gary R. and George P.E. (2002), “Application of Neuro System to behavior Representation in Computer generated forces”, retrieved http//:Cuil.com

Hiroshi S.; Kentaro K.; Kazuo O. and Masato O. (2011), “Statistical mechanics of Structural and temporal credit assignment effects on learning in neural Networks” retrieved from http://pre.aps.org/abstract/PRE/v83/i5/e051125.

Jionghua T.; Suhuan W.; Jingzhou Z. and Xue W. (2010), “Neuro-fuzzy logic based fusion algorithm of medical images" retrieved from http:// ieeexplore.ieee.org/xpl./freeabs_all.jsp ?

Leondes C. (2010), “The Technology of Fuzzy Logic Algorithm retrieved from Suite101.com/examples-of-expert-System-application-in-artificialIntelligience.

Mathers C.O. and Lancer D. (2006), Projections of global mortality and burden of disease from 2002 to 2030, Plus Medicine, 3: 2011-2030

NIJ: National Institute of Justice (2011), “Expert system technologies for criminal justice application” retrieved from https://www.ncjrs.gov/pdffiles1/nij/sl000959.pdf

PCAI (2000), “Expert System: Introduction, retrieved from http:// PCAI.com/web/ai_info/expert.systems.html

Ponniyin S.K. (2009), “Neural Network”, Icann2007.org/neural.networks.

Saman K. H. (2010), “Neuro-Fuzzy Systems from the Neural Network Perspective” retrieved from http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.39.857

Statsoft Incorporated (2008), “Neural Network” retrieved from http//: google.com.

Steffen L. (2011), “Expert system and local Computation”, University of Oxford, Graduate Lectures Hilary Term 2011

Stathacopoulou R.,Magoulas G.D.,Grigoriadou M., and Samarakou M. (2004), “A Neuro-Fuzzy Approach to Detect Student's Motivation, retrieved from http:// et.teiath.gr/English/cv/cv_samarakou.html –

Vahid K. and Gholam A.M. (2009), “Artificial Intelligence in medicines” V47, Issues 1 Information Technology Department, School of Engineering, Terbiat Moderas University Tehran, Iran.

WHO (2004), World Health Report; changing history. Geneva, World Health Organization.

Zadeh L.A. (1965), “Fuzzy sets. Information and control, Vol.8, pp.338-353.

Published
2015-05-02
How to Cite
Amadin, F., & J.C., O. (2015). Fuzzy-Neuropsychiatric Predictive Model. Journal of Biomedical Engineering and Medical Imaging, 2(2), 14. https://doi.org/10.14738/jbemi.22.1036