An open natural language processing (NLP) framework for EHR-based clinical research: a case demonstration using the National COVID Cohort Collaborative (N3C).
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| Title: | An open natural language processing (NLP) framework for EHR-based clinical research: a case demonstration using the National COVID Cohort Collaborative (N3C). |
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| Authors: | Liu S; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, Minnesota, USA., Wen A; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, Minnesota, USA., Wang L; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, Minnesota, USA., He H; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, Minnesota, USA., Fu S; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, Minnesota, USA., Miller R; Tufts Clinical and Translational Science Institute, Tufts Medical Center, Boston, Massachusetts, USA., Williams A; Tufts Clinical and Translational Science Institute, Tufts Medical Center, Boston, Massachusetts, USA., Harris D; Department of Internal Medicine, University of Kentucky, Lexington, Kentucky, USA., Kavuluru R; Department of Internal Medicine, University of Kentucky, Lexington, Kentucky, USA., Liu M; Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas, USA., Abu-El-Rub N; Department of Internal Medicine, University of Kansas Medical Center, Kansas City, Kansas, USA., Schutte D; Department of Pharmaceutical Care & Health Systems, University of Minnesota at Twin Cities, Minneapolis, Minnesota, USA., Zhang R; Department of Pharmaceutical Care & Health Systems, University of Minnesota at Twin Cities, Minneapolis, Minnesota, USA., Rouhizadeh M; Department of Pharmaceutical Outcomes & Policy, University of Florida, Gainesville, Florida, USA., Osborne JD; Department of Computer Science, University of Alabama at Birmingham, Birmingham, Alabama, USA., He Y; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan, USA., Topaloglu U; Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA., Hong SS; Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA., Saltz JH; Department of Biomedical Informatics, Stony Brook University, Stony Brook, New York, USA., Schaffter T; Sage Bionetwork, Seattle, Washington, USA., Pfaff E; Department of Medicine, University of North Carolina Chapel Hill, Chapel Hill, North Carolina, USA., Chute CG; Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA., Duong T; Department of Radiology, Albert Einstein College of Medicine, Bronx, New York, USA., Haendel MA; Center for Health AI, University of Colorado Anschutz Medical Campus, Denver, Colorado, USA., Fuentes R; Alex Informatics, North Bethesda, Maryland, USA., Szolovits P; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA., Xu H; School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, Texas, USA., Liu H; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, Minnesota, USA.; School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, Texas, USA. |
| Source: | Journal of the American Medical Informatics Association : JAMIA [J Am Med Inform Assoc] 2023 Nov 17; Vol. 30 (12), pp. 2036-2040. |
| Publication Type: | Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Oxford University Press Country of Publication: England NLM ID: 9430800 Publication Model: Print Cited Medium: Internet ISSN: 1527-974X (Electronic) Linking ISSN: 10675027 NLM ISO Abbreviation: J Am Med Inform Assoc Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1527-974X |
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| DOI: | 10.1093/jamia/ocad134 |
