Ascertainment of asthma prognosis using natural language processing from electronic medical records - 06/06/18
Doi : 10.1016/j.jaci.2017.12.1003
Sunghwan Sohn, PhD a, ∗, Chung-Il Wi, MD b, c, ∗, Stephen T. Wu, PhD d, Hongfang Liu, PhD a, Euijung Ryu, PhD a, Elizabeth Krusemark, AAS b, c, Alicia Seabright c, Gretchen A. Voge, MD e, Young J. Juhn, MD, MPH b, c 
a Department of Health Science Research, Mayo Clinic, Rochester, Minn
b Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minn
c Asthma Epidemiology Research Unit, Mayo Clinic, Rochester, Minn
d Oregon Health & Science University, Portland, Ore
e Division of Neonatology, Children's Hospitals and Clinics of Minnesota, Minneapolis, Minn
| This study was supported by the National Institutes of Health (NIH; grant no. R21AI116839-01). It was made possible by Rochester Epidemiology Project (grant no. R01-AG34676) from the National Institute on Aging and Center for Translational Science Activities (CTSA) grant (grant no. UL1 TR000135) from the National Center for Advancing Translational Sciences. Its contents are solely the responsibility of the authors and do not necessarily represent the official view of the NIH. |
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| Disclosure of potential conflict of interest: S. Sohn has received grants from the National Institute of Allergy and Infectious Diseases, the National Institute on Aging, and the National Center for Advancing Translational Sciences. Y. J. Juhn is the Principal Investigator of the Innovative Asthma Research Methods Award from Genentech. The rest of the authors declare that they have no relevant conflicts of interest. |
© 2018
American Academy of Allergy, Asthma & Immunology. Publié par Elsevier Masson SAS. Tous droits réservés.
Vol 141 - N° 6
P. 2292 - juin 2018 Retour au numéro
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