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Informatics Methods in Biomedicine: Foundations of a Profession. Post-doc. Clinical. Preclinical. Formal Mathematical, technical Ontology Database theory Signal processing Sequence analysis Formal grammars Process models Software engineering. Empirical
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Informatics Methods in Biomedicine: Foundations of a Profession
Post-doc Clinical Preclinical
Formal • Mathematical, technical • Ontology • Database theory • Signal processing • Sequence analysis • Formal grammars • Process models • Software engineering • Empirical • Cognitive, behavioral, organizational • Experimental design • Data modeling • Visualization • Decision analysis • Project management • User interface • Applied • A core set of methods for implementing and evaluating solutions • Deployment methods • Implementation issues • Assess impact
Computer Science • Can apply computational techniques to manage data,develop software and solve problems • Database Systems • Machine Learning • Programming and Problem Solving • Advanced Software Engineering
Statistics • Can apply mathematical techniques to analyze data and test hypotheses • Introduction to Biostatistics • Introduction to Biostatistical Methods
Biomedical • Is conversant with concepts, terminology, institutions, professionals, and methods of biomedical domain • Biochemistry and Molecular Biology • Acculturation to Medicine • Physiology • Epidemiology
Informatics Knowledge Is familiar with theories and results in Medical Informatics, and able to apply basic methods to solve problems • Methods in Medical Informatics (logic, decision science, cognitive science) • Introduction to Medical Informatics Applications
Informatics Methods • Logic • Formal Grammars • Ontology • Database theory • Decision Theory • Cognitive Analysis • Process Models • Measurement Theory
Data Representation • Can analyze, develop, and apply representations of biomedical data • Representation and Coding of Medical Data
Information Systems • Can analyze, develop, deploy and manage complex information systems • Health Information Systems Architecture • Introduction to Information Management
Information Presentation • Can analyze, develop, and deploy visual presentations of biomedical information • User Interfaces in Medicine • Understanding Information
Decision Making • Can analyze, develop, and apply formal models of biomedical decision making • Quantitative Models for Medical Decision Making and Clinical Support • Cognitive Sciences and Medical Informatics • Social and Economic Factors in Clinical Decision Making
Evaluation • Can analyze, plan and carry out formal evaluations of information systems • Evaluation Methods in Medical Informatics • Design of Medical Experiments • Introduction to Sociomedical Sciences Research Methods
Clinical Application Domain • Economics of Informatics • Project Management • Interactive Health Communications • Introduction to Databases and Data Mining
Imaging Application Domain • Biomedical Imaging • Analysis and Quantification of Medical Images • Wavelet Applications • Computation Neural Modeling and Neuroengineering
Bioinformatics Application Domain • Intro to Genomics • Computation Genomics • Sequence Analysis • Microarrays and Regulatory Networks • Biological Database
Public Health Application Domain • Use of Large Scale national health care data sets • Hospital Organization and Management • Health Communications
Biomedical Research Planning & Data Analysis Knowledge Acquisition Data Acquisition Model Development Image Generation Information Retrieval Treatment Planning Human Interface Diagnosis Teaching Applying Bioinformatics Knowledge to Research Areas Biomedical Knowledge Biomedical Data Real-time acquisition Imaging Speech/language/text Specialized input devices Machine learning Text interpretation Knowledge engineering Knowledge Base Data Base Inferencing System
Thanks to Dr. Stephen B. Johnson Dr. Ted Shortliffe