This application describes the Regenstrief Medical Informatics Research Fellowship Program, the mission of which is to prepare post-doctoral fellows for academic careers in medical informatics. Each year, a total of 3-4 fellows will be recruited into two-year fellowships. A few fellows will be given the option to extend to a third year. By participating in the didactic curriculum and Clinical Investigator Training Enhancement (CITE) masters degree program, research fellows will obtain a broad array of general research skills. Through the Medical Informatics curriculum, practicum experience, other lecture and discussion formats, and university course work they will gain competency in basic computer methods, they will improve their writing skills, learn the responsible conduct of research and the structure content and design of medical information systems, develop a general understanding of public health and clinical research informatics, and become familiar with the local data sets and computer systems on which they will base their research projects. Each fellow will be expected to gain competency in a modern programming language and database system so that they can understand the strengths and limits of the systems with which they work and be able to complete project work that requires some amount of programming. Fellows will be required to complete at least two projects, one of which must be an epidemiology/database research project. They will be expected to write up the plan in a form suitable for a grant application, and the results in a form suitable for publication. By the end of their second fellowship year, fellows will have performed a clinical epidemiologic project, designed and conducted a developmental research project, performed their own data analyses, and written papers to be submitted to peer-reviewed publications. Didactic teaching and mentors will be provided by the multidisciplinary faculty of the Regenstrief Institute representing the fields of medical informatics, public health informatics, health services research, decision science, bioinformatics and imaging informatics, behavioral medicine, clinical epidemiology, and biostatistics.

National Institute of Health (NIH)
National Library of Medicine (NLM)
Continuing Education Training Grants (T15)
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Special Emphasis Panel (ZLM1-AP-T (O1))
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Florance, Valerie
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Indiana University-Purdue University at Indianapolis
Schools of Medicine
United States
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Zhu, Vivienne J; Tu, Wanzhu; Rosenman, Marc B et al. (2014) A Comparison of Data Driven-based Measures of Adherence to Oral Hypoglycemic Agents in Medicaid Patients. AMIA Annu Symp Proc 2014:1294-301
Peng, Xiaodong; Wang, Fang; Li, Liwei et al. (2014) Exploring a structural protein-drug interactome for new therapeutics in lung cancer. Mol Biosyst 10:581-91
Fidahussein, Mustafa; Vreeman, Daniel J (2014) A corpus-based approach for automated LOINC mapping. J Am Med Inform Assoc 21:64-72
Klann, Jeffrey G; Szolovits, Peter; Downs, Stephen M et al. (2014) Decision support from local data: creating adaptive order menus from past clinician behavior. J Biomed Inform 48:84-93
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Klann, Jeffrey G; Anand, Vibha; Downs, Stephen M (2013) Patient-tailored prioritization for a pediatric care decision support system through machine learning. J Am Med Inform Assoc 20:e267-74
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Imler, Timothy D; Morea, Justin; Kahi, Charles et al. (2013) Natural language processing accurately categorizes findings from colonoscopy and pathology reports. Clin Gastroenterol Hepatol 11:689-94
Swaminathan, Shanker; Shen, Li; Risacher, Shannon L et al. (2012) Amyloid pathway-based candidate gene analysis of [(11)C]PiB-PET in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Brain Imaging Behav 6:1-15
Rajput, Zeshan A; Mbugua, Samuel; Amadi, David et al. (2012) Evaluation of an Android-based mHealth system for population surveillance in developing countries. J Am Med Inform Assoc 19:655-9

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