Credits: 3 (3-0-0)
Prerequisites: 90 Credits for UG students. For PG students with mathematics till 10+2 level only, bridge course (BMV702) is compulsory.
Overlaps with: BML800, BML735, MAL503/517/100, CHL761, MEL707, MTL108, MTL390, COL341/774, ELL409/784, SBL701, MSL892
Description
Overview of biomedical data and its analysis. Basics of statistics in relation to biomedical data analysis. This will cover learning about data distributions, continuous and discrete data, data representation (histogram, box and whisker plot, etc.) normality test, descriptive statistics (mean, standard-deviation, mode, kurtosis, etc.), inferential statistics (t-test, F-test, etc.), receiver-operating-characteristic (ROC)
curve analysis, correlations, etc. Pre-processing of data, qualitative, and quantitative analysis. Applications of mathematics in biomedical data analysis, including mathematical modeling, simulations, data fitting, and error analysis. Data compression and separation using SVD, PCA and ICA. Applications of Fourier transforms, Laplace transform, Basics of machine learning and its application in biomedical data analysis. Basics of machine learning: feature, normalization, training, validation and testing, data prediction, regression, data classification, classifiers, logistic regression, support-vector-machine, random forest classifier, feature selection, and optimization of parameters of classifiers. Advanced machine learning approaches (neural network, deep learning, etc.) and their applications in biomedical data analysis.
Prerequisite Tree
flowchart TD
BML738-1302[BML738]
BML738-1302 --> EC90-1302[EC90]
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