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Carol Friedman

Affiliations: 
Biomedical Informatics Columbia University, New York, NY 
Area:
natural language processing, sublanguage
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"Carol Friedman"
Cross-listing: Computational Biology Tree

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Parents

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Ralph Grishman grad student NYU

Children

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Paola K. Tulipano grad student 2007 Columbia
Hua Xu grad student 2008 Columbia
Jung-Wei Fan grad student 2009 Columbia
Yves A. Lussier post-doc 2001 Columbia (Plant Biology Tree)

Collaborators

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Naomi Sager collaborator Columbia
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Publications

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Liu C, Ta CN, Rogers JR, et al. (2019) Ensembles of Natural Language Processing Systems for Portable Phenotyping Solutions. Journal of Biomedical Informatics. 103318
Weng C, Hao T, Friedman C, et al. (2019) Crowdsourcing Public Opinion for Sharing Medical Records for the Advancement of Science. Studies in Health Technology and Informatics. 264: 1393-1397
Weng C, Friedman C, Rommel CA, et al. (2019) A two-site survey of medical center personnel's willingness to share clinical data for research: implications for reproducible health NLP research. Bmc Medical Informatics and Decision Making. 19: 70
Son JH, Xie G, Yuan C, et al. (2018) Deep Phenotyping on Electronic Health Records Facilitates Genetic Diagnosis by Clinical Exomes. American Journal of Human Genetics
Vilar S, Friedman C, Hripcsak G. (2017) Detection of drug-drug interactions through data mining studies using clinical sources, scientific literature and social media. Briefings in Bioinformatics
Salmasian H, Tran TH, Chase HS, et al. (2015) Medication-indication knowledge bases: a systematic review and critical appraisal. Journal of the American Medical Informatics Association : Jamia
Li Y, Ryan PB, Wei Y, et al. (2015) A Method to Combine Signals from Spontaneous Reporting Systems and Observational Healthcare Data to Detect Adverse Drug Reactions. Drug Safety. 38: 895-908
Xu H, Aldrich MC, Chen Q, et al. (2015) Validating drug repurposing signals using electronic health records: a case study of metformin associated with reduced cancer mortality. Journal of the American Medical Informatics Association : Jamia. 22: 179-91
Li Y, Salmasian H, Vilar S, et al. (2014) A method for controlling complex confounding effects in the detection of adverse drug reactions using electronic health records. Journal of the American Medical Informatics Association : Jamia. 21: 308-14
Salmasian H, Freedberg DE, Friedman C. (2013) Deriving comorbidities from medical records using natural language processing. Journal of the American Medical Informatics Association : Jamia. 20: e239-42
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