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}

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  address = {New York},
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}

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}

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@article{haendel_2020,
  author = {Haendel, Melissa A and Chute, Christopher G and Bennett, Tellen D and Eichmann, David A and Guinney, Justin and Kibbe, Warren A and Payne, Philip R O and Pfaff, Emily R and Robinson, Peter N and Saltz, Joel H and Spratt, Heidi and Suver, Christine and Wilbanks, John and Wilcox, Adam B and Williams, Andrew E and Wu, Chunlei and Blacketer, Clair and Bradford, Robert L and Cimino, James J and Clark, Marshall and Colmenares, Evan W and Francis, Patricia A and Gabriel, Davera and Graves, Alexis and Hemadri, Raju and Hong, Stephanie S and Hripscak, George and Jiao, Dazhi and Klann, Jeffrey G and Kostka, Kristin and Lee, Adam M and Lehmann, Harold P and Lingrey, Lora and Miller, Robert T and Morris, Michele and Murphy, Shawn N and Natarajan, Karthik and Palchuk, Matvey B and Sheikh, Usman and Solbrig, Harold and Visweswaran, Shyam and Walden, Anita and Walters, Kellie M and Weber, Griffin M and Zhang, Xiaohan Tanner and Zhu, Richard L and Amor, Benjamin and Girvin, Andrew T and Manna, Amin and Qureshi, Nabeel and Kurilla, Michael G and Michael, Sam G and Portilla, Lili M and Rutter, Joni L and Austin, Christopher P and Gersing, Ken R and the N3C Consortium },
  title = "{The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment}",
  journal = {Journal of the American Medical Informatics Association},
  volume = {28},
  number = {3},
  pages = {427-443},
  year = {2020},
  month = {08},
  abstract = "{Coronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers.The Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics.Organized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access.The N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19.}",
  issn = {1527-974X},
  doi = {10.1093/jamia/ocaa196},
  url = {https://doi.org/10.1093/jamia/ocaa196},
  eprint = {https://academic.oup.com/jamia/article-pdf/28/3/427/37306721/ocaa196.pdf},
}

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@article {li_2023,
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@article{madlock_brown_2022b,
  author = {Madlock-Brown, C. and Wilkens, K. and Weiskopf, N. and Cesare, N. and Bhattacharyya, S. and Riches, N. O. and Espinoza, J. and Dorr, D. and Goetz, K. and Phuong, J. and Sule, A. and Kharrazi, H. and Liu, F. and Lemon, C. and Adams, W. G.},
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}

@article{mehta_2021,
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}

@article{mitra_2023,
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}

@article{morgan_2018,
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}

@article{narrett_2023,
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}

@book{ohdsi_2019,
  title = {The Book of OHDSI: Observational Health Data Sciences and Informatics},
  author = {OHDSI},
  isbn = {9781088855195},
  url = {https://ohdsi.github.io/TheBookOfOhdsi/},
  address = {United States},
  year = {2019},
  publisher = {OHDSI}
}

@misc{palantir_2023,
  title = {Documentation: Code repositories overview},
  author = {Palantir},
  howpublished = "\url{https://www.palantir.com/docs/foundry/code-repositories/overview/}",
  year = {2023},
  note = "[Online; accessed 2023-03-14]"
}

@article{pfaff_2022a,
  title = {Identifying who has long COVID in the USA: a machine learning approach using N3C data.},
  author = {Pfaff, E. R.  and Girvin, A. T.  and Bennett, T. D.  and Bhatia, A.  and Brooks, I. M.  and Deer, R. R.  and Dekermanjian, J. P.  and Jolley, S. E.  and Kahn, M. G.  and Kostka, K.  and McMurry, J. A.  and Moffitt, R.  and Walden, A.  and Chute, C. G.  and Haendel, M. A.  and Bramante, C.  and Dorr, D.  and Morris, M.  and Parker, A. M.  and Sidky, H.  and Gersing, K.  and Hong, S.  and Niehaus, E.},
  year = {2022},
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  doi = {10.1016/S2589-7500(22)00048-6},
  journal = {Lancet Digit Health},
  month = may,
  pages = {e532-e541},
  numpages = {10}
}

@article{pfaff_2022b,
  title = {Synergies between centralized and federated approaches to data quality: a report from the national COVID cohort collaborative},
  author = {Pfaff, Emily R and Girvin, Andrew T and Gabriel, Davera L and Kostka, Kristin and Morris, Michele and Palchuk, Matvey B and Lehmann, Harold P and Amor, Benjamin and Bissell, Mark and Bradwell, Katie R and others},
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  year = {2022},
  doi = {10.1093/jamia/ocab217},
  publisher = {Oxford University Press}
}

@article{pfaff_2023a,
  title = {Coding long COVID: characterizing a new disease through an ICD-10 lens},
  author = {Pfaff, Emily R and Madlock-Brown, Charisse and Baratta, John M and Bhatia, Abhishek and Davis, Hannah and Girvin, Andrew and Hill, Elaine and Kelly, Elizabeth and Kostka, Kristin and Loomba, Johanna and others},
  journal = {BMC medicine},
  volume = {21},
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  year = {2023},
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  publisher = {BioMed Central}
}

@article{redelmeier_2023,
  author = {Redelmeier, D. A. and Wang, J. and Thiruchelvam, D.},
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  doi = {10.1016/j.amjmed.2022.11.002},
  url = {https://www.ncbi.nlm.nih.gov/pubmed/36470796},
  year = {2023},
  type = {Journal Article}
}

@article{reese_2023,
  title = {Generalisable long COVID subtypes: Findings from the NIH N3C and RECOVER programmes},
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}

@article{richesson_2013,
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}

@article{schneeweiss_2019,
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}

@article{schuemie_2018,
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}

@article{schuemie_2020,
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  title = {Large-scale evidence generation and evaluation across a network of databases (LEGEND): assessing validity using hypertension as a case study},
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}

@article{sharafeldin_2021,
  author = {Sharafeldin, Noha and Bates, Benjamin and Song, Qianqian and Madhira, Vithal and Yan, Yao and Dong, Sharlene and Lee, Eileen and Kuhrt, Nathaniel and Shao, Yu Raymond and Liu, Feifan and Bergquist, Timothy and Guinney, Justin and Su, Jing and Topaloglu, Umit},
  title = {Outcomes of COVID-19 in Patients With Cancer: Report From the National COVID Cohort Collaborative (N3C)},
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  volume = {39},
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}

@article{sidky_2023,
  author = {Sidky, H. and Young, J. C. and Girvin, A. T. and Lee, E. and Shao, Y. R. and Hotaling, N. and Michael, S. and Wilkins, K. J. and Setoguchi, S. and Funk, M. J. and Consortium, N. C.},
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}

@article{stoudt_2021,
  author = {Stoudt, S. and Vasquez, V. N. and Martinez, C. C.},
  title = {Principles for data analysis workflows},
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}

@article{sun_2022,
  title = "Association Between Immune Dysfunction and COVID-19 Breakthrough Infection After SARS-CoV-2 Vaccination in the US",
  author = "Jing Sun and Qulu Zheng and Vithal Madhira and Olex, {Amy L.} and Anzalone, {Alfred J.} and Amanda Vinson and Singh, {Jasvinder A.} and Evan French and Abraham, {Alison G.} and Jomol Mathew and Nasia Safdar and Gaurav Agarwal and Fitzgerald, {Kathryn C.} and Namrata Singh and Umit Topaloglu and Chute, {Christopher G.} and Mannon, {Roslyn B.} and Kirk, {Gregory D.} and Patel, {Rena C.}",
  note = "Funding Information: tools through the N3C Data Enclave (ncats.nih.gov/ n3c/about), which is supported by grant U24 TR002306 from National Center for Advancing Translational Sciences (NCATS). National COVID Cohort Collaborative (N3C) is funded by grant U24 TR002306 from NCATS. Ms Olex and Mr French were supported by Clinical and Translational Science Awards UL1TR002649 from NCATS. Mr Anzalone was supported by grants U54GM104942-05S2 and U54GM115458 from National Institute of General Medical Sciences, which funds the West Virginia Clinical & Translational Science Institute and the Great Plains IDeA Clinical and Translational Research Network. Dr Safdar was supported by grant DP2AI144244 from National Institute of Allergy and Infectious Diseases (NIAID) and by a grant from the US Department of Veterans Affairs. Dr N. Singh was supported in part by grant DP2AI144244 from NIAID. Dr Kirk was supported in part by grant K24AI118591 from NIAID. Dr Patel was supported by grant K23AI120855 from NIAID. Funding Information: reported receiving grants from Paladin Labs Inc and personal fees from Paladin Labs Inc advisory board outside the submitted work. Dr J.A. Singh reported receiving personal fees from Crealta/Horizon, Medisys, Fidia, PK Med, Two Labs Inc, Adept Field Solutions, Clinical Care Options, ClearView Healthcare Partners, Putnam Associates, Focus Forward, Navigant, Spherix, MedIQ, Jupiter Life Science, UBM LLC, Trio Health, Medscape, WebMD, Practice Point Communications, National Institutes of Health (NIH), American College of Rheumatology, and Simply Speaking; holding stock options from TPT Global Tech, Vaxart Pharmaceuticals, Atyu Biopharma, and Charlotte's Web Holdings Inc outside the submitted work. Dr Abraham reported receiving grants from NIH and personal fees from Implementation Group Inc outside the submitted work. Dr Topaloglu reported being a stockholder of CareDirections LLC. Dr Chute reported receiving grants from NIH outside the submitted work. Dr Mannon reported serving as a steering committee member for IMAGINE trial from Vitaeris; receiving honorarium as deputy editor of American Journal of Transplantation; grants from Mallinckrodt Pharmaceuticals, and grants to institution for clinical trial from CSL Behring, Transplant Genomics, and Quark Pharmaceuticals outside the submitted work; and serving as chair of Policy and Advocacy Committee of American Society of Nephrology and co-chair of review committee of Scientific Registry of Transplant Recipients. No other disclosures were reported. Publisher Copyright: {\textcopyright} 2021 American Medical Association.",
  year = "2022",
  month = feb,
  doi = "10.1001/jamainternmed.2021.7024",
  language = "English (US)",
  volume = "182",
  pages = "153--162",
  journal = "Archives of internal medicine (Chicago, Ill. : 1908)",
  issn = "2168-6106",
  publisher = "American Medical Association",
  number = "2",
}

@article{tan_2023,
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}

@misc{usfda_2017,
  author = {{U.S. Food and Drug Administration}},
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}

@misc{usfda_2019,
  author = {{U.S. Food and Drug Administration and the Duke-Margolis Center for Health Policy}},
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@article{usfda_2021,
  author = {{U.S. Food and Drug Administration, Health Canada, and the United Kingdom's Medicines and Healthcare products Regulatory Agency (MHRA)}},
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@techreport{usfda_2023,
  author = {{U.S. Food and Drug Administration}},
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@article{wang_2021,
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}

@article{weiskopf_2023,
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  url = {https://www.ncbi.nlm.nih.gov/pubmed/36752649},
  year = {2023},
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}

@Book{wickham_2022,
  title = {R for Data Science},
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}

@article{wilkinson_2016,
  title = {The FAIR Guiding Principles for scientific data management and stewardship},
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  biburl = {https://www.bibsonomy.org/bibtex/284ff5b88120fbf405870b49cf7e60767/joschirr},
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  doi = {10.1038/sdata.2016.18}
}

@InCollection{xie_2014,
  booktitle = {Implementing Reproducible Computational Research},
  author = {Yihui Xie},
  editor = {Victoria Stodden and Friedrich Leisch and Roger D. Peng},
  title = {knitr: A Comprehensive Tool for Reproducible Research in {R}},
  publisher = {Chapman and Hall/CRC},
  year = {2014},
  isbn = {978-1466561595},
  url = {http://www.crcpress.com/product/isbn/9781466561595},
}

@Book{xie_2015,
  title = {Dynamic Documents with {R} and knitr},
  author = {Yihui Xie},
  publisher = {Chapman and Hall/CRC},
  address = {Boca Raton, Florida},
  year = {2015},
  edition = {2nd},
  isbn = {978-1498716963},
  url = {http://yihui.org/knitr/},
}

@Book{xie_2016,
  title = {bookdown: Authoring Books and Technical Documents with {R} Markdown},
  author = {Yihui Xie},
  publisher = {Chapman and Hall/CRC},
  address = {Boca Raton, Florida},
  year = {2016},
  isbn = {978-1138700109},
  url = {https://bookdown.org/yihui/bookdown},
}

@Book{xie_2018,
  title = {R Markdown: The Definitive Guide},
  author = {Yihui Xie and J.J. Allaire and Garrett Grolemund},
  publisher = {Chapman and Hall/CRC},
  address = {Boca Raton, Florida},
  year = {2018},
  isbn = {978-1138359338},
  url = {https://bookdown.org/yihui/rmarkdown},
}

@Book{xie_2020,
  title = {R Markdown Cookbook},
  author = {Yihui Xie and Christophe Dervieux and Emily Riederer},
  publisher = {Chapman and Hall/CRC},
  address = {Boca Raton, Florida},
  year = {2020},
  isbn = {9780367563837},
  url = {https://bookdown.org/yihui/rmarkdown-cookbook},
}

@article{yang_2021,
  title = {Associations between HIV infection and clinical spectrum of COVID-19: a population level analysis based on US National COVID Cohort Collaborative (N3C) data},
  author = {Yang, Xueying and Sun, Jing and Patel, Rena C and Zhang, Jiajia and Guo, Siyuan and Zheng, Qulu and Olex, Amy L and Olatosi, Bankole and Weissman, Sharon B and Islam, Jessica Y and others},
  journal = {The Lancet HIV},
  volume = {8},
  number = {11},
  pages = {690--700},
  year = {2021},
  doi = {10.1016/S2352-3018(21)00239-3},
  publisher = {Elsevier}
}

@article{zhou_2022,
  author = {Zhou, R. and Johnson, K. E. and Rousseau, J. F. and Rathouz, P. J. and Consortium, N. C.},
  title = {Comparative Effectiveness of Dexamethasone in Treatment of Hospitalized COVID-19 Patients during the First Year of the Pandemic: The N3C Data Repository},
  journal = {medRxiv},
  doi = {10.1101/2022.10.22.22281373},
  url = {https://www.ncbi.nlm.nih.gov/pubmed/36324806},
  year = {2022},
  type = {Journal Article}
}
# Book References to add
# * Python & Spark

# Useful tools:
# The "Cite" link for entries in https://scholar.google.com/
# https://www.bioinformatics.org/texmed/