NDLI: Building a neuro-fuzzy model for predicting the bacteria bound and internalized by the white blood cells

Content Provider	IEEE Xplore Digital Library
Author	Kaur, D. Sangtani, J.
Copyright Year	2009
Description	Author affiliation: University of Toledo, USA (Kaur, D.; Sangtani, J.)
Abstract	In this paper, a model to reflect the immunological properties of white blood cells is created. White blood cells kill infectious bacteria. Two kinds of white blood cells — CHO-IIA and THP1 are studied. Bacteria of sizes 5μm and 0.05μm, and an amount of catalytic agent MβCD is added to the white blood cell. Experiments are conducted first by keeping the bacteria size fixed and varying the amount of MβCD to observe their effects on bacteria bound to a cell, and then bacteria internalized by a cell. Later the same experiment is repeated with a different bacteria size. The data collected is used to create a model with inbuilt rules, based on fuzzy logic. The model is trained with back propagation using neuro-fuzzy techniques, in order to improve the model. The results obtained by the model are compared with the actual observed data to compare the efficiency of the model. With training, the Root Mean Squared Error reduced from 0.4099 to 0.3705. Complete software with a Graphical User Interface is built to easily display the output of the model, from user-given input.
Starting Page	211
Ending Page	216
File Size	545644
Page Count	6
File Format	PDF
ISBN	9781424433544
DOI	10.1109/EIT.2009.5189613
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-07
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Predictive models Microorganisms White blood cells Cells (biology) Immune system Graphical user interfaces Chemicals Displays Antibiotics Fuzzy logic GUI Neuro-Fuzzy modeling White Blood Cells
Content Type	Text
Resource Type	Article

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