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Information Extraction from biomedical texts

Information Extraction from biomedical texts. Mohammed Alshayeb 11/16/2009. Rules. Order of Rules. High frequency appearance come first. More evidences are needed. Domains. Domains have verbs. e.g. studies/MM-DRUG_CHEMICAL_COMPOUND_THERAPEUTIC_MODALITY/VB

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Information Extraction from biomedical texts

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  1. Information Extraction from biomedical texts Mohammed Alshayeb 11/16/2009

  2. Rules

  3. Order of Rules • High frequency appearance come first. • More evidences are needed.

  4. Domains • Domains have verbs. • e.g. studies/MM-DRUG_CHEMICAL_COMPOUND_THERAPEUTIC_MODALITY/VB • So far Pattern Matcher expects domains have only names.

  5. Example • Sentence: tpck/MM-MOLECULE/NN or L-NAME causes hemorrhagic_shock/MM-CONDITION/NN • Dependency: nsubj(causes-4, tpck/MM-MOLECULE/NN-5) -- dobj(case-4,hemorrhagic_shock/MM-CONDITION/NN-7) • Match: case-4(tpck/MM-MOLECULE/NN-5, hemorrhagic_shock/MM-CONDITION/NN-7)

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