Informatics for Integrating Biology and the Bedside (I2B2) addresses one of the central bottlenecks in translating findings and hypotheses in model systems or organisms into studies and findings relevant to improving human health: the difficulty in conducting clinical research that makes use of all the possibilities afforded by the full array of new information provided by genomic research. I2B2's scalable computational and organizational framework for conducting clinical research in and across large multidisciplinary academic medical centers is designed for the establishment of a """"""""new"""""""" biomedicine that both (a) fully exploits the fruit of the genomic revolution for clinical practice and (b) allows clinical care to be leveraged to advance basic biological research. We have chosen as our laboratory the entirety of a leading, large academic healthcare system: Partners Healthcare as well as other hospitals affiliated with Harvard Medical School. Among our investigators are the leaders in information technology, clinical research, biological research and genomic research at these hospitals. We have adopted collaborative and administrative structures based on decade long histories of multi-disciplinary research, notably at the Division of Health Sciences and Technology of Harvard and MIT. These are matched with Driving Biology Projects championed by leading clinical researchers in diabetes mellitus, neurological disease, airways disease and hypertension brought together for the first time by these structures and opportunities. The models of collaboration as well as the tools, computational methodologies and educational programs will be widely disseminated through the I2B2 dissemination core and through specifically targeted programs for underrepresented minorities.

Agency
National Institute of Health (NIH)
Institute
National Library of Medicine (NLM)
Type
Specialized Center--Cooperative Agreements (U54)
Project #
5U54LM008748-03
Application #
7104383
Study Section
Special Emphasis Panel (ZRG1-BST-A (55))
Program Officer
Florance, Valerie
Project Start
2004-09-15
Project End
2009-07-31
Budget Start
2006-08-01
Budget End
2007-07-31
Support Year
3
Fiscal Year
2006
Total Cost
$3,956,000
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
Yu, Zhi; Kim, Seoyoung C; Vanni, Kathleen et al. (2018) Association between inflammation and systolic blood pressure in RA compared to patients without RA. Arthritis Res Ther 20:107
Agniel, Denis; Kohane, Isaac S; Weber, Griffin M (2018) Biases in electronic health record data due to processes within the healthcare system: retrospective observational study. BMJ 361:k1479
Yu, Sheng; Ma, Yumeng; Gronsbell, Jessica et al. (2018) Enabling phenotypic big data with PheNorm. J Am Med Inform Assoc 25:54-60
Luo, Yuan; Wang, Fei; Szolovits, Peter (2017) Tensor factorization toward precision medicine. Brief Bioinform 18:511-514
Luo, Yuan; Uzuner, Özlem; Szolovits, Peter (2017) Bridging semantics and syntax with graph algorithms-state-of-the-art of extracting biomedical relations. Brief Bioinform 18:160-178
Luo, Yuan (2017) Recurrent neural networks for classifying relations in clinical notes. J Biomed Inform 72:85-95
Nanba, Kazutaka; Vaidya, Anand; Williams, Gordon H et al. (2017) Age-Related Autonomous Aldosteronism. Circulation 136:347-355
Kim, Youngjun; Riloff, Ellen; Meystre, Stéphane M (2017) Exploiting Unlabeled Texts with Clustering-based Instance Selection for Medical Relation Classification. AMIA Annu Symp Proc 2017:1060-1069
Bigdeli, T B; Ripke, S; Peterson, R E et al. (2017) Genetic effects influencing risk for major depressive disorder in China and Europe. Transl Psychiatry 7:e1074
Hundemer, Gregory L; Baudrand, Rene; Brown, Jenifer M et al. (2017) Renin Phenotypes Characterize Vascular Disease, Autonomous Aldosteronism, and Mineralocorticoid Receptor Activity. J Clin Endocrinol Metab 102:1835-1843

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