Health Informatics and Bioinformatics | College of Information Sciences and Technology
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Health Informatics and Bioinformatics

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About: Health Informatics is concerned with the design, development, evaluation, adoption, and application of Health Information Technology (HIT) innovations in healthcare services delivery, management, and planning aiming to improve access to, quality, outcomes, and efficiency of healthcare. Bioinformatics is concerned with the development and applications of informatics methods and tools for analysis, interpretation, modeling, and visualization of complex biological data (including molecular sequence, structure, expression, and interaction Fundata). Brain informatics is concerned with the development and applications of informatics tools and methods for analysis, interpretation, modeling, and visualization of brain data (including connectivity, activity, and behavior).

Areas of Strength: Some areas of strength in Bioinformatics include the development of effective tools for analysis and prediction of protein-protein, protein-RNA, protein-DNA interfaces and interactions, for predicting epitopes and designing vaccines, and for annotating genomes. Some areas of focus in brain informatics include the development and application of methods for analysis and interpretation of brain connectivity and activity data (especially Functional Magnetic Resonance Imaging (fMRI) and Electroencephalogram (EEG) data). Some areas of strength in Health Informatics include development and application of methods and tools for integrative analyses of electronic health records, genomic, and contextual (socio-economic, environmental, and demographic) data for predictive and causal modeling of health outcomes, personalized treatments, design and evaluation of personal and mobile health (mHealth) applications for real time monitoring and detection for heart attack, stress, sleep quality, fall and other medical conditions, healthcare systems engineering, human-centered design interventions, text analytics, network analytics, and machine learning to improve health services delivery.

Faculty: John M. Carroll, Chao-Hsien Chu, Vasant Honavar, Sharon Huang, John Yen