ABSTRACT
This chapter focuses on data processing and biosensor modeling. It follows the “hands-on modeling” approach, i.e., how to get results from equations. Principal component analysis (PCA) is based on the eigenvalue analysis. The result of PCA is to transform data to a new set of variables and reduce the dimensionality of data. Consider the medical data that are used to differentiate benign and malignant breast cancer. MatLab dataset for breast cancer will be used. Neural network are computing systems inspired by the biological neural networks that constitute animal brains. Neural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. The MatLab breast cancer dataset is used as the input data. Two physical processes are analyzed in simulation of enzyme biosensor: enzyme kinetics and diffusion. The chapter provides the readers some ability to solve the one-dimensional diffusion equation and modify it to solve biosensor simulations.
