BM4012 Data Analytics for Healthcare Technologies Syllabus:
BM4012 Data Analytics for Healthcare Technologies Syllabus – Anna University PG Syllabus Regulation 2021
COURSE OBJECTIVES:
To explore the various forms of electronic health care information.
To learn the techniques adopted to analyse health care data.
To understand the natural language based analytics
To understand the predictive models for clinical data
To gain knowledge health care analytics and its applications
UNIT I INTRODUCTION
Introduction to Healthcare Data Analytics- Electronic Health Records–Components of EHR- Coding Systems- Benefits of EHR- Barrier to Adopting EHR-Challenges- Phenotyping Algorithms.
UNIT II DATA ANALYSIS
Biomedical Image Analysis- Mining of Sensor Data in Healthcare- Biomedical Signal Analysis Genomic Data Analysis for Personalized Medicine
UNIT III ANALTICS
Natural Language Processing and Data Mining for Clinical Text- Mining the Biomedical -Social Media Analytics for Healthcare.
UNIT IV ADVANCED ANALYTICS
Advanced Data Analytics for Healthcare– Review of Clinical Prediction Models- Temporal Data Mining for Healthcare Data- Visual Analytics for Healthcare- Predictive Models for Integrating Clinical and Genomic Data- Information Retrieval for Healthcare- Privacy- Preserving Data Publishing Methods in Healthcare
UNIT V APPLICATIONS
Applications and Practical Systems for Healthcare– Data Analytics for Pervasive Health Fraud Detection in Healthcare- Data Analytics for Pharmaceutical Discoveries- Clinical Decision Support Systems- Computer-Assisted Medical Image Analysis Systems- Mobile Imaging and Analytics for Biomedical Data.
TOTAL PERIODS: 45
PRACTICAL EXERCISES: 30 PERIODS
1. Study of open source software
2. Data storage and retrieval on software
3. Creation of electronic patient record
4. Web page creation using HTML
5. Preprocessing the given dataset
6. User interface design
7. Univariate and Multivariate regression
8 Classification techniques
COURSE OUTCOMES:
CO1: Understand about health care analytics and benefits of Electronic health records.
CO2: Understand about Bio medical image analysis
CO3: Understand about Natural language processing and biomedical mining
CO4: Understand about information retrieval for health care.
CO5: Demonstrate about applications and practical systems for health care.
TOTAL: 75 PERIODS
REFERENCES
1. Chandan K. Reddy and Charu C Aggarwal, “Healthcare data analytics”, Taylor & Francis, 2015
2. Hui Yang and Eva K. Lee, “Healthcare Analytics: From Data to Knowledge to Healthcare Improvement, Wiley, 2016.
3. Michael Berthold, David J.Hand, “Intelligent Data Analysis”, Springer, 2007.
4. David J. Lubliner , “Biomedical Informatics: An Introduction to Information Systems and Software in Medicine and Health”, CRC Press, Boca Raton, 2016