Extracting medication information from unstructured public health data: a demonstration on data from population-based and tertiary-based samples.

Chen, Robert; Ho, Joyce C; Lin, Jin-Mann S

Chen, Robert; Ho, Joyce C; Lin, Jin-Mann S.

Affiliation

Chen R; Chronic Viral Diseases Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, 1600 Clifton Rd. NE, Mailstop H24-12, Atlanta, GA, 30329, USA.
Ho JC; School of Medicine, Emory University, 1648 Pierce Dr NE, Atlanta, GA, 30307, USA.
Lin JS; Chronic Viral Diseases Branch, Division of High-Consequence Pathogens and Pathology, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, 1600 Clifton Rd. NE, Mailstop H24-12, Atlanta, GA, 30329, USA.

BMC Med Res Methodol ; 20(1): 258, 2020 10 15.

Article in En | MEDLINE | ID: mdl-33059588

Subject(s)

Natural Language Processing; Public Health; Data Mining; Electronic Health Records; Humans; Machine Learning

Key words

Automation; Co-morbidity; Data extraction; Medication; Mylagic encephalomyelitis/chronic fatigue syndrome (ME/CFS); Natural language processing; Population; Tertiary; Unstructured data

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Natural Language Processing / Public Health Type of study: Guideline Aspects: Determinantes_sociais_saude Limits: Humans Language: En Journal: BMC Med Res Methodol Journal subject: MEDICINA Year: 2020 Document type: Article Affiliation country: United States

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