An Intelligent Decision Support Tool for Early Diagnosis of Functional Pituitary Adenomas

Volume: 5 Number: 2 December 1, 2015
EN

An Intelligent Decision Support Tool for Early Diagnosis of Functional Pituitary Adenomas

Abstract

In this work, a web based integrated Medical Decision Support System MDSS tool for mainly early diagnosis of functional pituitary adenomas i.e., somatotrophinoma, corticotrophinoma and prolactinoma is developed. In the MDSS tool, hormone diseases are described by means of well-classified set of attributes generated from the typical sign and symptoms of disorders.The proposed tool is based on a stationary linear stochastic system model which specifically predicts the selected hormone diseases employing certain system parameters. The MDSS tool is user friendly which includes questions and answers at the opening session of the self-test. Questions and answers session will be completed by “yes” or “no” type of simple-responses. Based on our clinical results, MDSS tool yields more than 99% correct decisions on the selected hormone diseases. It is expected that effective use of the proposed MDSS tool will save substantial amount of valuable time of an expert endocrinologists and minimizes the cost of diagnosis. Furthermore, it will provide the opportunity for early diagnosis for the patient and the expert medical doctor to take the necessary preventive measures

Keywords

References

  1. [1] Ryan, J., (2010), A history of the Internet and the digital future, Reaktion, London, UK.
  2. [2] Handbook of Medical Informatics, http://www.mieur.nl/mihandbook/r 3 3/handbook/home.htm.
  3. [3] Reichertz, P. L., (2006), Hospital information systems-past, present, future, International Journal of Medical Informatics, vol.75, issues 3-4, pp. 282-289.
  4. [4] Burstein, F and Carlsson, S., (2008), Decision support through knowledge management, in Handbook on Decision Support Systems 1: Basic Themes, eds Frada Burstein and Clyde W. Holsapple, pp. 103-120, Springer-Verlag, Berlin Germany.
  5. [5] Gaynor, M, Seltzer, M., Moulton, S. and Freedman, J., (2006), A dynamic, data-driven, decision support system for emergency medical services, International Conference on Computational Science, 2, pp. 703-711.
  6. [6] Zerger, A. and Smith, D. I., (2003), Impediments to using GIS for real-time disaster decision support, Computers, Environment and Urban Systems, 27, pp. 123-141.
  7. [7] Zhu, S., Abraham, J., Paul, S. A., Reddy, M., Yen, J., Pfaff, M. and DeFlitch, C., (2007), R-CASTMED: Applying intelligent agents to support emergency medical decision making teams, in Proc. of the 11th Conference on Artificial Intelligence in Medicine (AIME2007), pp. 34-41, Amsterdam, Netherlands.
  8. [8] Yarman, B. S., et al, (2006), Multi-dimensional system approach to assess the outcome of human interacted events, Proceedings of 17th International Symposium of Mathematical Theory of Networks and Systems, pp. 799-802, Kyoto, Japan.

Details

Primary Language

English

Subjects

-

Journal Section

-

Authors

S. L. Karaman This is me

S. Yarman This is me

B. S. Yarman This is me

Publication Date

December 1, 2015

Submission Date

-

Acceptance Date

-

Published in Issue

Year 2015 Volume: 5 Number: 2

APA
Gökbay, I. Z., Karaman, S. L., Yarman, S., & Yarman, B. S. (2015). An Intelligent Decision Support Tool for Early Diagnosis of Functional Pituitary Adenomas. TWMS Journal of Applied and Engineering Mathematics, 5(2), 169-187. https://izlik.org/JA36PK59RF
AMA
1.Gökbay IZ, Karaman SL, Yarman S, Yarman BS. An Intelligent Decision Support Tool for Early Diagnosis of Functional Pituitary Adenomas. JAEM. 2015;5(2):169-187. https://izlik.org/JA36PK59RF
Chicago
Gökbay, I. Z., S. L. Karaman, S. Yarman, and B. S. Yarman. 2015. “An Intelligent Decision Support Tool for Early Diagnosis of Functional Pituitary Adenomas”. TWMS Journal of Applied and Engineering Mathematics 5 (2): 169-87. https://izlik.org/JA36PK59RF.
EndNote
Gökbay IZ, Karaman SL, Yarman S, Yarman BS (December 1, 2015) An Intelligent Decision Support Tool for Early Diagnosis of Functional Pituitary Adenomas. TWMS Journal of Applied and Engineering Mathematics 5 2 169–187.
IEEE
[1]I. Z. Gökbay, S. L. Karaman, S. Yarman, and B. S. Yarman, “An Intelligent Decision Support Tool for Early Diagnosis of Functional Pituitary Adenomas”, JAEM, vol. 5, no. 2, pp. 169–187, Dec. 2015, [Online]. Available: https://izlik.org/JA36PK59RF
ISNAD
Gökbay, I. Z. - Karaman, S. L. - Yarman, S. - Yarman, B. S. “An Intelligent Decision Support Tool for Early Diagnosis of Functional Pituitary Adenomas”. TWMS Journal of Applied and Engineering Mathematics 5/2 (December 1, 2015): 169-187. https://izlik.org/JA36PK59RF.
JAMA
1.Gökbay IZ, Karaman SL, Yarman S, Yarman BS. An Intelligent Decision Support Tool for Early Diagnosis of Functional Pituitary Adenomas. JAEM. 2015;5:169–187.
MLA
Gökbay, I. Z., et al. “An Intelligent Decision Support Tool for Early Diagnosis of Functional Pituitary Adenomas”. TWMS Journal of Applied and Engineering Mathematics, vol. 5, no. 2, Dec. 2015, pp. 169-87, https://izlik.org/JA36PK59RF.
Vancouver
1.I. Z. Gökbay, S. L. Karaman, S. Yarman, B. S. Yarman. An Intelligent Decision Support Tool for Early Diagnosis of Functional Pituitary Adenomas. JAEM [Internet]. 2015 Dec. 1;5(2):169-87. Available from: https://izlik.org/JA36PK59RF