In this article, we are going to discuss the B.E. Biomedical Engineering, semester VI, Anna University connected to the regulation 2021 subject syllabus. Let’s see what’s more…
We tried our best to provide the following unit-wise BM3651 – Fundamentals Of Healthcare Analytics detailed Syllabus. We sum up the appropriate textbooks and references to this page. If you have any doubts regarding the syllabus, you can simply comment below on the following page. Hope this information is useful. Share it with your classmates. Thanks for landing on this page.
If you want to know more about the B.E. Biomedical Engineering Syllabus connected to an affiliated institution’s four-year undergraduate degree program. We provide you with a detailed Year-wise, semester-wise, and Subject-wise syllabus in the following link B.E. Biomedical Engineering Syllabus Regulation 2021 Anna University.
Aim of Concept:
The objective of this course is to enable the student to
- Understand the statistical methods for the design of biomedical research.
- Comprehend the fundamental of mathematical and statistical theory in the application of Healthcare.
- Apply the regression and correlation analyze in the healthcare data.
- Understand the Meta analysis and variance analysis.
- Interpret the results of the investigational methods.
BM3651 – Fundamentals Of Healthcare Analytics Syllabus
Unit I: Introduction
Introduction, Computers and bio statistical analysis, Introduction to probability, likelihood & odds, distribution variability. Finding the statistical distribution using appropriate software tool like R/ Python.
Unit II: Statistical Parameters
Statistical parameters p-values, computation, level chi square test and distribution and hypothesis testing -single population proportion, difference between two population proportions, single population variance, tests of homogeneity. Testing of statistical parameters using appropriate software R / Python.
Unit III: Regression And Correlation Analysis
Regression model, evaluating the regression equation, correlation model, correlation coefficient. Finding regression, correlation for the data using appropriate software like R / Python.
Unit IV: Analysis Of Variance
META analysis for research activities, purpose and reading of META analysis, kind of data used for META analysis, completely randomized design, randomized complete block design, repeated measures design, factorial experiment. Testing the variance using appropriate software tool like R / Python.
Unit V: Case Studies
Epidemical reading and interpreting of epidemical studies, application in community health, Case study on Medical Imaging like MRI, CT. Case study on respiratory data, Case study on ECG data.
Text Books:
- Wayne W. Daniel, Biostatistics-A Foundation for Analysis in the Health Sciences, John Wiley & Sons Publication, 10th Edition, 2013.
- Peter Armotage, Geoffrey Berry and J.N.S.Mathews, Statistical methods in Medical Research, Wiley-Blackwell, 4th Edition, 2001.
- Bernard Rosner. Fundamentals of biostatistics. Nelson Education, 8th Edition 2015 ISBN:978- 1 -305-26892-0
References:
- Marcello Pagano and Kimberlee Gauvreu, Principles of Biostatistics, Chapman and Hall/CRC, 2nd Edition, 2018.
- Ronald N Forthofer and EunSul Lee, Introduction to Biostatistics, Academic Press, 1st Edition, 2014.
- Animesh K. Dutta, Basic Biostatistics and its Applications, New Central Book Agency, 1st Edition, 2006.
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