EC887 Biomedical Data Science

Course Name: 

EC887 Biomedical Data Science

Programme: 

M.Tech(SPML)

Category: 

Elective (Ele)

Credits (L-T-P): 

(3-0-2) 4

Content: 

Physiological signals and responses, Bioelectrical signals, Evoked potentials, Electromyogram, respiration and heart rate variability, mathematical modelling and techniques for image and bio-signal analysis and diagnostic decisionmaking, detection, classification techniques, Medical and microscopy image analysis, Heterogeneous data integration and Electronic Medical Records (EHR), Explainable Artificial Intelligence (AI) applications in the biomedical field, Medical data sets and annotating, cleaning, organizing, storing, and analysing, knowledge discovery, Genomics Data Analysis.

References: 

Jaakko Malmivuo, Bioelectromagnetism - Principles and Applications of Bioelectric and Biomagnetic Fields, Oxford University Press, 1995.
John L. Semmlow, Benjamin Griffel, Biosignal and Medical Image Processing, 3rd Ed, CRC Press, 2014.
Rangayyan R M, S Krishnan, Biomedical Signal Analysis 3rd Edition, Wiley 2023.
Michael Insana, Biomedical Measurement Systems and Data Science, Cambridge University Press, 2021.
Tore Samuelsson, Genomics and Bioinformatics: An Introduction to Programming Tools for Life Scientists, Cambridge University Press, 2012.

Department: 

Electronics and Communication Engineering(ECE)
 

Contact us

Prof. Ramesh Kini M.
Professor and Head,
Department of ECE, NITK, Surathkal,
P. O. Srinivasnagar,
Mangalore - 575 025 Karnataka, India.

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