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Overview of Biomedical Informatics Rakesh Nagarajan.

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1 Overview of Biomedical Informatics Rakesh Nagarajan

2 Clinical Research Needs Data Integration Analysis Visualization Participant Recruitment/ Biospecimen Selection

3 Population-based Research Needs Data Integration Analysis Visualization Study Health Records Disseminate Clinical Practice Modifications Identify clinical/pharmacologic factors adversely affecting patient health care

4 What is Biomedical Informatics? Bench ScienceComputer Science MedicineMathematics/Biostatistics Biomedical Informatics

5 What is Biomedical Informatics? Public Health Informatics

6 What is Biomedical Informatics? Public Health Informatics Aspects of public health informatics  Vital statistics  Communicable disease cases  Immunization records  Emergency room data  Insurance data sets  Geographical information systems Adapted from http://en.wikipedia.org/wiki/Public_health_informaticshttp://en.wikipedia.org/wiki/Public_health_informatics

7 What is Biomedical Informatics? Public Health Informatics Medical Informatics

8 What is Biomedical Informatics? Public Health Informatics Medical Informatics Aspects of medical informatics  Collection of electronic health record information  Natural language processing  Medical decision making  Decision support systems Adapted from http://en.wikipedia.org/wiki/Clinical_informaticshttp://en.wikipedia.org/wiki/Clinical_informatics

9 What is Biomedical Informatics? Public Health Informatics Medical Informatics Imaging/Pathology Informatics 1 Image source: http://www.aperio.com/imageanalysis/image-analysis.asphttp://www.aperio.com/imageanalysis/image-analysis.asp 2 Image source: http://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpghttp://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpg 12

10 What is Biomedical Informatics? Public Health Informatics Medical Informatics Imaging/Pathology Informatics 1 Image source: http://www.aperio.com/imageanalysis/image-analysis.asphttp://www.aperio.com/imageanalysis/image-analysis.asp 2 Image source: http://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpghttp://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpg 12 Aspects of imaging/pathology informatics  Image/report de-identification algorithms  Automation of image processing engines  Discrete quantification of image components (e.g. brain regions or nuclear size)

11 What is Biomedical Informatics? Public Health Informatics Medical Informatics Imaging/Pathology Informatics Bioinformatics 1 Image source: http://www.aperio.com/imageanalysis/image-analysis.asphttp://www.aperio.com/imageanalysis/image-analysis.asp 2 Image source: http://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpghttp://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpg 12

12 What is Biomedical Informatics? Public Health Informatics Medical Informatics Imaging/Pathology Informatics Bioinformatics 1 Image source: http://www.aperio.com/imageanalysis/image-analysis.asphttp://www.aperio.com/imageanalysis/image-analysis.asp 2 Image source: http://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpghttp://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpg 12 Aspects of bioinformatics  Development of computational algorithms  In silico analysis of high dimensional, molecular profiling data sets  Integration of genome annotation information  Prediction of gene relational networks

13 Relationships of Basic Data Types Patient Participant

14 Integration of Clinical and Research Systems Inpatient Data Patient Participant Outpatient Data Imaging Data Clinical Research Data Clinical Studies Data Biospecimen Data Research Imaging Data Molecular and Genomic Data Integrated Data Analysis and Visualization

15 Integration of Clinical and Research Systems Inpatient Data Patient Participant Outpatient Data Imaging Data Clinical Research Data Clinical Studies Data Biospecimen Data Research Imaging Data Molecular and Genomic Data Integrated Data Analysis and Visualization Data integration requires that software systems are interoperable with each other

16 What is Interoperability? Semantic interoperability Syntactic interoperability  in·ter·op·er·a·bil·i·ty  ability of a system...to use the parts or equipment of another system Source: Merriam-Webster web site  interoperability  ability of two or more systems or components to exchange information and to use the information that has been exchanged. Source: IEEE Standard Computer Dictionary: A Compilation of IEEE Standard Computer Glossaries, IEEE, 1990

17  Syntactic interoperability- Use of standardized programming interfaces  Semantic interoperability  Use of controlled vocabularies and ontologies  Unique concept codes for each term  One or more textual representations  Examples  LOINC- Laboratory tests  SNOMED- Clinical terms (e.g. diagnoses)  CPT- Medical procedures  RxNORM- Medications Facilitating Interoperability

18  cancer Biomedical Informatics Grid (caBIG®)  Domain Workspaces  Clinical Trials  Tissue Banking and Technology Tools  Integrative Cancer Research  In Vivo Imaging  Population Science  Cross-cutting Workspaces  Vocabularies and Common Data Elements  Architecture National and Global Data Integration

19  Clinical and Translational Science Award (CTSA)  Clinical Research Repositories  Education  Collaboration Facilitation (Research Networking) National and Global Data Integration

20 Course Lectures Public Health Informatics Medical Informatics Imaging/Pathology Informatics Bioinformatics 1 Image source: http://www.aperio.com/imageanalysis/image-analysis.asphttp://www.aperio.com/imageanalysis/image-analysis.asp 2 Image source: http://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpghttp://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpg 12 Lectures 2-8

21 Course Lectures Public Health Informatics Medical Informatics Imaging/Pathology Informatics Bioinformatics 1 Image source: http://www.aperio.com/imageanalysis/image-analysis.asphttp://www.aperio.com/imageanalysis/image-analysis.asp 2 Image source: http://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpghttp://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpg 12 Lecture 9

22 Course Lectures Public Health Informatics Medical Informatics Imaging/Pathology Informatics Bioinformatics 1 Image source: http://www.aperio.com/imageanalysis/image-analysis.asphttp://www.aperio.com/imageanalysis/image-analysis.asp 2 Image source: http://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpghttp://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpg 12 Lectures 10-11

23 Course Lectures Public Health Informatics Medical Informatics Imaging/Pathology Informatics Bioinformatics 1 Image source: http://www.aperio.com/imageanalysis/image-analysis.asphttp://www.aperio.com/imageanalysis/image-analysis.asp 2 Image source: http://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpghttp://www.spectroscopynow.com/FCKeditor/UserFiles/Image/$pectroscopyNOW_ezines_2009/SN45a/SN45a_M_alz(1).jpg 12 Lectures 12-14

24 Course Labs Inpatient Data Patient Participant Outpatient Data Imaging Data Clinical Research Data Clinical Studies Data Biospecimen Data Research Imaging Data Molecular and Genomic Data Integrated Data Analysis and Visualization CIDER ClinPortal Tissue Suite

25 Course Labs  CIDER- Learn how to use the electronic health record for research purposes  ClinPortal and Tissue Suite- Learn best practices and the process of clinical studies and biospecimen data management  Complete a research project that employs the above tools  Ongoing project or assigned

26 Course Grading  25% laboratory quizzes  25% laboratory short assignments  50% project presentation

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