Health Natural Language Processing Center (hNLP Center) center.healthnlp.org Guergana K. Savova, PhD Associate Professor Boston Children’s Hospital Harvard Medical School Guergana.Savova@childrens.harvard.edu Noemie Elhadad, PhD Associate Professor Columbia University Noemie.Elhadad@columbia.edu Martha Palmer, PhD Professor University of Colorado, Boulder Martha.Palmer@colorado.edu

Support National Institutes of Health National Library of Medicine National Institute of General Medical Sciences National Cancer Institute Office of the National Coordinator of Healthcare Technology Support – Mayo Clinic, Boston Children’s Hospital Institutions contributing de-identified clinical notes Cincinnati's Children’s Hospital and Medical Center Mayo Clinic UPMC Beth Israel Current funding – NIGMS R01GM114355 (Extended Methods and Software Development for Health NLP)

hNLP Center: Mission Support health language-related education, research and technology development by creating and sharing curated linguistic textual resources based on the principle that broad access to data drives innovation.

hNLP Center: Organizational Structure Not-for-profit consortium of members Advisory Committee to strategically guide its trajectory Rebecca Jacobson, UPMC Piet de Groen, University of Minnesota/Mayo Clinic Mark Liberman, University of Pennsylvania/Linguistic Data Consortium John Brownstein, Boston Children’s Hospital/Harvard Medical School Dina Demner-Fushman, National Library of Medicine John Pestian, Cincinnati’s Children’s Hospital and Medical Center Fee-based membership to ensure its sustainability Industry members obtain a commercial license

hNLP Center: Activities Provide a repository and data curation, distribution and management point for health-related language resources Support sponsored research programs and health-related language-based technology evaluations Engage in collaborations with US and foreign researchers, institutions and data centers Host and participate in various workshops.

hNLP Center: Roadmap through 2020 Distribution of about 2M words of clinical text with layers of linguistic gold annotation (constituency trees, dependency trees, coreference, temporal relations, events) domain gold annotations (clinical entities with mappings to ontologies, clinical data elements). These datasets have already been created with funding from the National Institutes of Health Portions released for shared tasks to advance science CLEF/ShARe (http://clefehealth2014.dcu.ie/) SemEval Analysis of Clinical Text (http://alt.qcri.org/semeval2014/task7/ ; http://alt.qcri.org/semeval2015/task14/) SemEval Clinical TempEval (http://alt.qcri.org/semeval2015/task6/; http://alt.qcri.org/semeval2016/task12/ )

Sample Gold Annotations: Layers The patient underwent a CT scan in April which did not reveal lesions in his liver. Boundary Detection … The patient underwent a CT scan in April which did not reveal lesions in his liver. The patient underwent a CT scan in April which did not reveal lesions his liver . - undergo do lesion DT NN VBD IN NNP WDT RB VB NNS PRP$ Tokenization Normalization Part-of-speech Tagger CT scan Lesion Liver Procedure Disease / Disorder Anatomy UMLS ID: C0040405 UMLS ID: C0022198 UMLS ID: C0023884 Biomedical End-Use Entity Recognition Chunking NP VP PP … undergo.01 ( A1.patient; A2.scan; AM-TEMP.in ) reveal.01 ( A0.scan; R-A0.which; AM-NEG.not; A1.lesions; AM-LOC.in ) … Constituency Parsing S NP DT NN VP … Dependency Parsing SRL CT scan Lesion Liver Negated: no Negated: yes Subject: patient -- Entity Properties Biomedical End-Use UMLS Relation locationOf ( lesions, liver ) Event, Temp. Expr. CT scan April Reveal Lesions April CONTAINS CT scan CT scan CONTAINS lesions Temporal Relation Coreference identity ( the patient, his )

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