Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/4400
Title: Modeling and simulation of biosensor arrays for automated cancer detection
Researcher: Ushaa, S M
Guide(s): Madhavi Latha, M
Madhusudhan Rao, G
Keywords: Bio Sensors
Automated Drug Delivery System
Healthcare
RFID Devices
Human Diseases
Prostate Cancer Treatment
Ovarian Cancer Treatment
DNA Sensors
Feed-Forward Artificial Neural Networks (FFANN)
Upload Date: 24-Aug-2012
University: Jawaharlal Nehru Technological University
Completed Date: May 2011
Abstract: Drug dosing is a technique that is done to cure the diseases through proper prescription and control of drugs that have been identified to the corresponding disease based on diagnosis. Drug dosing is a very critical and challenging step that needs to be correctly monitored and prescribed by the doctor. Drug dosing in human beings also depends upon size, area, weight and volume of the recipient. There are various ways of drug dosing, targeted therapies are the current state of the art and are probably the best predictor in terms of perceiving the dosing. Nanobio systems are used for targeted therapies. Food and Drug Administration (FDA) has recommended the use of nanobio systems for targeted therapy and drug dosing but they do not have many models. In reality very few exist. With limitations in availability of common platforms for development and validation of automated systems there is a need for a new methodology or integration of multiple platforms to integrate biosensors, expert system and drug diffusion unit. In this research work, it is proposed to develop a methodology for integrating biosensor models from nanohub.org and Matlab. The model for nanowire based sensor may be developed using basic principles and can be characterized using experimental setup. Sensor array model consisting of 64 nanowires is proposed to develop to detect prostate cancer. A control unit that triggers the sensor array may be developed and can be used in measuring the concentration of analyte solution. The location of nanowirecan be distributed using Gaussian distribution function. A new sensor array consisting of planar sensor and nanowire sensor may be developed to increase the sensitivity of the system in detecting prostate cancer. Expert system based on feed forward neural network architecture may be designed and modeled for ovarian cancer classification. A two layered network consisting of sigmoid transfer function and purelin function may be designed.
Pagination: xiv, 246p.
URI: http://hdl.handle.net/10603/4400
Appears in Departments:Department of Electronics and Communication Engineering

Files in This Item:
File Description SizeFormat 
01_title.pdfAttached File138.12 kBAdobe PDFView/Open
02_declaration.pdf164.53 kBAdobe PDFView/Open
03_certificates.pdf170.15 kBAdobe PDFView/Open
04_dedication.pdf107.92 kBAdobe PDFView/Open
05_acknowledgements.pdf150.11 kBAdobe PDFView/Open
06_abstract.pdf150.28 kBAdobe PDFView/Open
07_contents.pdf221.71 kBAdobe PDFView/Open
08_list of figures.pdf162.09 kBAdobe PDFView/Open
09_list of tables.pdf148.89 kBAdobe PDFView/Open
10_nomenclature.pdf202.06 kBAdobe PDFView/Open
11_abbreviations.pdf190.42 kBAdobe PDFView/Open
12_chapter 1.pdf373.83 kBAdobe PDFView/Open
13_chapter 2.pdf596.77 kBAdobe PDFView/Open
14_chapter 3.pdf402.33 kBAdobe PDFView/Open
15_chapter 4.pdf892.31 kBAdobe PDFView/Open
16_chapter 5.pdf681.12 kBAdobe PDFView/Open
17_chapter 6.pdf689.27 kBAdobe PDFView/Open
18_chapter 7.pdf330.43 kBAdobe PDFView/Open
19_chapter 8.pdf210.23 kBAdobe PDFView/Open
20_references.pdf286.61 kBAdobe PDFView/Open
21_appendix.pdf547.96 kBAdobe PDFView/Open


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