The University of Pittsburgh proposes a five-year renewal of its training program in Biomedical Informatics. The T15 grant is currently entering its 25th consecutive year. Our program is notable for the long and distinguished history of biomedical informatics research in Pittsburgh, the continuous evolution and refinement of our educational programs, the strong institutional commitment to biomedical informatics and our training program, and the rich biomedical and computational research environment in which our training program is set. The program has an administrative home in the Department of Biomedical Informatics (DBMI) within the University of Pittsburgh School of Medicine. DBMI provides space, equipment, and financial support for training program administration, faculty, graduate students and postdoctoral scholars. The program is supported by an interdepartmental core faculty of 29 faculty members, including all 17 faculty members with primary appointments in DBMI. The Training Program Director, a tightly knit leadership group of faculty co- directors, and two experienced staff members support the overall operation of the program. The Pittsburgh BMI Training Program offers research training in all four sub-disciplines of Biomedical Informatics: translational bioinformatics, clinical research informatics, healthcare/clinical informatics, and public health informatics. Additionally, we also offer specialized research training in dental informatics. Students in our T15-funded training program may pursue an MS or PhD in Biomedical Informatics, an MS or PhD in Intelligent Systems - Biomedical Informatics Track, an MD/PhD through the Medical Scientist Training Program, or advanced postdoctoral research. The training program has undergone significant enhancements during the past funding period including a new core curriculum, improved advising structure, improved program evaluation plan, and enhanced efforts to recruit trainee candidates, including candidates from under-represented minorities and disadvantaged backgrounds. Enhancements for the proposed funding period include new advanced graduate seminars, new professional development content, and enhanced training in the responsible conduct of research. We have a strong track record of success in training biomedical informatics researchers in all sub- disciplines. Trainees from our program are publishing research articles in high impact journals in the field, winning national awards for their research, writing successful K grants and individual fellowship awards, and securing research positions in academics, industry and government upon graduation.

Public Health Relevance

hisgrantproposesthecontinuation ofthUeniversity ofPittsburh tanngpogam nBomedcl Inomatcs.Thegrant would supportpredoctoral ndpostdoctoa studesfo eigbecnddtes nteestedinpusungreserchcreesinbomedclinomatcs.Thepogam ofesreserchtan in theappiction ofinormtcstoprobemsintansatonl scences, cinclscseancrecsh,cinclr andpublichealth.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Continuing Education Training Grants (T15)
Project #
3T15LM007059-27S1
Application #
8845378
Study Section
Special Emphasis Panel (ZLM1-AP-T (01))
Program Officer
Florance, Valerie
Project Start
1987-07-01
Project End
2017-06-30
Budget Start
2013-07-01
Budget End
2014-06-30
Support Year
27
Fiscal Year
2014
Total Cost
$32,163
Indirect Cost
$2,382
Name
University of Pittsburgh
Department
Miscellaneous
Type
Schools of Medicine
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Liu, Yuzhe; Gopalakrishnan, Vanathi (2017) An Overview and Evaluation of Recent Machine Learning Imputation Methods Using Cardiac Imaging Data. Data (Basel) 2:
Posada, Jose D; Barda, Amie J; Shi, Lingyun et al. (2017) Predictive modeling for classification of positive valence system symptom severity from initial psychiatric evaluation records. J Biomed Inform 75S:S94-S104
Furtado, Andre D; Ceschin, Rafael; Bl├╝ml, Stefan et al. (2017) Neuroimaging of Peptide-based Vaccine Therapy in Pediatric Brain Tumors: Initial Experience. Neuroimaging Clin N Am 27:155-166
Aronis, John M; Millett, Nicholas E; Wagner, Michael M et al. (2017) A Bayesian system to detect and characterize overlapping outbreaks. J Biomed Inform 73:171-181
Warburton, Andrew J; Boone, David N (2017) Insights from Global Analyses of Long Noncoding RNAs in Breast Cancer. Curr Pathobiol Rep 5:23-34
King, Andrew J; Fisher, Arielle M; Becich, Michael J et al. (2017) Computer Science, Biology and Biomedical Informatics academy: Outcomes from 5 years of Immersing High-school Students into Informatics Research. J Pathol Inform 8:2
King, Andrew J; Hochheiser, Harry; Visweswaran, Shyam et al. (2017) Eye-tracking for clinical decision support: A method to capture automatically what physicians are viewing in the EMR. AMIA Jt Summits Transl Sci Proc 2017:512-521
Schabdach, Jenna; Wells 3rd, William M; Cho, Michael et al. (2017) A Likelihood-Free Approach for Characterizing Heterogeneous Diseases in Large-Scale Studies. Inf Process Med Imaging 10265:170-183
Ye, Ye; Wagner, Michael M; Cooper, Gregory F et al. (2017) A study of the transferability of influenza case detection systems between two large healthcare systems. PLoS One 12:e0174970
Lustgarten, Jonathan Lyle; Balasubramanian, Jeya Balaji; Visweswaran, Shyam et al. (2017) Learning Parsimonious Classification Rules from Gene Expression Data Using Bayesian Networks with Local Structure. Data (Basel) 2:

Showing the most recent 10 out of 174 publications