NLP Fundamentals: Methods and Shared Lexical Resources

1. NLP Fundamentals: Methods and Shared Lexical Resources GuerganaSavova, PhD Boston Childrens Hospital and Harvard Medical School

2. Overview • Clinical Element Model (CEM) templates as normalization targets for SHARP NLP • NLP areas of research • Methods • Shared Lexical Resources

3. CEMs as NLP Normalization Target

5. Processing Clinical Notes A 43-year-old woman was diagnosed with type 2 diabetes mellitus by her family physician 3 months before this presentation. Her initial blood glucose was 340 mg/dL. Glyburide 2.5 mg once daily was prescribed. Since then, self-monitoring of blood glucose (SMBG) showed blood glucose levels of 250-270 mg/dL. She was referred to an endocrinologist for further evaluation. On examination, she was normotensive and not acutely ill. Her body mass index (BMI) was 18.7 kg/m2 following a recent 10 lb weight loss. Her thyroid was symmetrically enlarged and ankle reflexes absent. Her blood glucose was 272 mg/dL, and her hemoglobin A1c (HbA1c) was 10.3%. A lipid profile showed a total cholesterol of 261 mg/dL, triglyceride level of 321 mg/dL, HDL level of 48 mg/dL, and an LDL of 150 mg/dL. Thyroid function was normal. Urinanalysis showed trace ketones. She adhered to a regular exercise program and vitamin regimen,smoked 2 packs of cigarettes daily for the past 25 years, and limited her alcohol intake to 1 drink daily. Her mother's brother was diabetic. A 43-year-old woman was diagnosed with type 2 diabetes mellitus by her family physician 3 months before this presentation. Her initial blood glucose was 340 mg/dL. Glyburide 2.5 mg once daily was prescribed. Since then, self-monitoring of blood glucose (SMBG) showed blood glucose levels of 250-270 mg/dL. She was referred to an endocrinologist for further evaluation. On examination, she was normotensive and not acutely ill. Her body mass index (BMI) was 18.7 kg/m2 following a recent 10 lb weight loss. Her thyroid was symmetrically enlarged and ankle reflexes absent. Her blood glucose was 272 mg/dL, and her hemoglobin A1c (HbA1c) was 10.3%. A lipid profile showed a total cholesterol of 261 mg/dL, triglyceride level of 321 mg/dL, HDL level of 48 mg/dL, and an LDL of 150 mg/dL. Thyroid function was normal. Urinanalysis showed trace ketones. She adhered to a regular exercise program and vitamin regimen, smoked 2 packs of cigarettes daily for the past 25 years, and limited her alcohol intake to 1 drink daily. Her mother's brother was diabetic. A 43-year-old woman was diagnosed with type 2 diabetes mellitus by her family physician 3 months before this presentation. Her initial blood glucose was 340 mg/dL. Glyburide A 43-year-old woman was diagnosed with type 2 diabetes mellitus by her family physician 3 mpresentation. Her initial blood glucose was 340 mg/dL. Glyburide A 43-year-old woman was diagnosed with type 2 diabetes mellitus by her family physician 3 months before this presentation. Her initial blood glucose was 340 mg/dL. Glyburide

6. Clinical Element Model Disorder CEM text: diabetes mellitus code: 73211009 subject: patient relative temporal context: 3 months ago negation indicator: not negated A 43-year-old woman was diagnosed with type 2 diabetes mellitus by her family physician 3 months before this presentation. Her initial blood glucose was 340 mg/dL. Glyburide 2.5 mg once daily was prescribed. Since then, self-monitoring of blood glucose (SMBG) showed blood glucose levels of 250-270 mg/dL. She was referred to an endocrinologist for further evaluation. On examination, she was normotensive and not acutely ill. Her body mass index (BMI) was 18.7 kg/m2 following a recent 10 lb weight loss. Her thyroid was symmetrically enlarged and ankle reflexes absent. Her blood glucose was 272 mg/dL, and her hemoglobin A1c (HbA1c) was 10.3%. A lipid profile showed a total cholesterol of 261 mg/dL, triglyceride level of 321 mg/dL, HDL level of 48 mg/dL, and an LDL of 150 mg/dL. Thyroid function was normal. Urinanalysis showed trace ketones. She adhered to a regular exercise program and vitamin regimen,smoked 2 packs of cigarettes daily for the past 25 years, and limited her alcohol intake to 1 drink daily.Her mother's brother was diabetic. A 43-year-old woman was diagnosed with type 2 diabetes mellitus by her family physician 3 months before this presentation.Her initial blood glucose was 340 mg/dL. Glyburide 2.5 mg once daily was prescribed. Since then, self-monitoring of blood glucose (SMBG) showed blood glucose levels of 250-270 mg/dL. She was referred to an endocrinologist for further evaluation. On examination, she was normotensive and not acutely ill. Her body mass index (BMI) was 18.7 kg/m2 following a recent 10 lb weight loss. Her thyroid was symmetrically enlarged and ankle reflexes absent. Her blood glucose was 272 mg/dL, and her hemoglobin A1c (HbA1c) was 10.3%. A lipid profile showed a total cholesterol of 261 mg/dL, triglyceride level of 321 mg/dL, HDL level of 48 mg/dL, and an LDL of 150 mg/dL. Thyroid function was normal. Urinanalysis showed trace ketones. She adhered to a regular exercise program and vitamin regimen,smoked 2 packs of cigarettes daily for the past 25 years, and limited her alcohol intake to 1 drink daily.Her mother's brother was diabetic. A 43-year-old woman was diagnosed with type 2 diabetes mellitus by her family physician 3 months before this presentation.Her initial blood glucose was 340 mg/dL. Glyburide 2.5 mg once daily was prescribed. Since then, self-monitoring of blood glucose (SMBG) showed blood glucose levels of 250-270 mg/dL. She was referred to an endocrinologist for further evaluation. On examination, she was normotensive and not acutely ill. Her body mass index (BMI) was 18.7 kg/m2 following a recent 10 lb weight loss. Her thyroid was symmetrically enlarged and ankle reflexes absent. Her blood glucose was 272 mg/dL, and her hemoglobin A1c (HbA1c) was 10.3%. A lipid profile showed a total cholesterol of 261 mg/dL, triglyceride level of 321 mg/dL, HDL level of 48 mg/dL, and an LDL of 150 mg/dL. Thyroid function was normal. Urinanalysis showed trace ketones. She adhered to a regular exercise program and vitamin regimen,smoked 2 packs of cigarettes daily for the past 25 years, and limited her alcohol intake to 1 drink daily.Her mother's brother was diabetic. A 43-year-old woman was diagnosed with type 2 diabetes mellitus by her family physician 3 months before this presentation.Her initial blood glucose was 340 mg/dL. Glyburide 2.5 mg once daily was prescribed. Since then, self-monitoring of blood glucose (SMBG) showed blood glucose levels of 250-270 mg/dL. She was referred to an endocrinologist for further evaluation. On examination, she was normotensive and not acutely ill. Her body mass index (BMI) was 18.7 kg/m2 following a recent 10 lb weight loss. Her thyroid was symmetrically enlarged and ankle reflexes absent. Her blood glucose was 272 mg/dL, and her hemoglobin A1c (HbA1c) was 10.3%. A lipid profile showed a total cholesterol of 261 mg/dL, triglyceride level of 321 mg/dL, HDL level of 48 mg/dL, and an LDL of 150 mg/dL. Thyroid function was normal. Urinanalysis showed trace ketones. She adhered to a regular exercise program and vitamin regimen, smoked 2 packs of cigarettes daily for the past 25 years, and limited her alcohol intake to 1 drink daily.Her mother's brother was diabetic. Medication CEM text: Glyburide code: 315989 subject: patient frequency: once daily negation indicator: not negated strength: 2.5 mg Tobacco Use CEM text: smoking code: 365981007 subject: patient relative temporal context: 25 years negation indicator: not negated Disorder CEM text: diabetes mellitus code: 73211009 subject: family member relative temporal context: negation indicator: not negated

7. Comparative Effectiveness Disorder CEM text: diabetes mellitus code: 73211009 subject: patient relative temporal context: 3 months ago negation indicator: not negated Compare the effectiveness of different treatment strategies (e.g., modifying target levels for glucose, lipid, or blood pressure) in reducing cardiovascular complications in newly diagnosed adolescents and adults with type 2 diabetes. Compare the effectiveness of traditional behavioral interventions versus economic incentives in motivating behavior changes (e.g., weight loss, smoking cessation, avoiding alcohol and substance abuse) in children and adults. Medication CEM text: Glyburide code: 315989 subject: patient frequency: once daily negation indicator: not negated strength: 2.5 mg Tobacco Use CEM text: smoking code: 365981007 subject: patient relative temporal context: 25 years negation indicator: not negated Disorder CEM text: diabetes mellitus code: 73211009 subject: family member relative temporal context: negation indicator: not negated

8. Meaningful Use Disorder CEM text: diabetes mellitus code: 73211009 subject: patient relative temporal context: 3 months ago negation indicator: not negated • Maintain problem list • Maintain active med list • Record smoking status • Provide clinical summaries for each office visit • Generate patient lists for specific conditions • Submit syndromic surveillance data Medication CEM text: Glyburide code: 315989 subject: patient frequency: once daily negation indicator: not negated strength: 2.5 mg Tobacco Use CEM text: smoking code: 365981007 subject: patient relative temporal context: 25 years negation indicator: not negated Disorder CEM text: diabetes mellitus code: 73211009 subject: family member relative temporal context: negation indicator: not negated

9. Clinical Practice Disorder CEM text: diabetes mellitus code: 73211009 subject: patient relative temporal context: 3 months ago negation indicator: not negated • Provide problem list and meds from the visit Medication CEM text: Glyburide code: 315989 subject: patient frequency: once daily negation indicator: not negated strength: 2.5 mg

10. Applications • Meaningful use of the EMR • Comparative effectiveness • Clinical investigation • Patient cohort identification • Phenotype extraction • Epidemiology • Clinical practice • …..

11. The Science of NLP: Research Areas

12. NLP Areas of Research • Part of speech tagging • Parsing – constituency and dependency • Predicate-argument structure (semantic role labeling) • Named entity recognition • Word sense disambiguation • Relation discovery and classification • Discourse parsing (text cohesiveness) • Language generation • Machine translation • Summarization • Creating datasets to be used for learning • a.k.a. computable gold annotations • Active learning

13. Methods • Principled approaches • Linguistic theory • Computational science • Machine Learning • Supervised • Unsupervised • Lightly supervised • Rules derived by domain experts • Combination • How to integrate knowledge-based information with data-driven methods

14. Applications (all apply to biomedicine) • Information extraction “No evidence of adenocarcinoma.” • Disorder • Text: adenocarcinoma • Associated code: C0001418 • Certainty: confirmed • Context: current • Subject: patient • Status: negated • Information retrieval • Question answering • Document classification • Input for • Decision support systems • Recommender systems • ….

15. Shared Lexical Resources

16. Why • Developing algorithms • System evaluation • Community-wide training and test sets • Compare results and establish state-of-the-art • Establishing standards (ISO TC37) • Long tradition in the general NLP domain • Linguistic Data Consortium and PTB • Layers of annotations on the same text

17. Available gold annotations: clinical narrative • MiPACQ • 120K words of clinical narrative • Layers of annotations – pos tags, treebanking, propbanking, UMLS entities and modifiers, UMLS relations and modifiers, coreference • ShARe (Shared Annotated Resources) • 500K words of clinical narrative • Layers of annotations – pos tags, phrasal chunks, UMLS entity mentions of type Disease/Disorder and modifiers • i2b2 shared tasks • Medication • Coreference

18. Available gold annotations (cont.) • SHARPn • 500K words of clinical narrative • Layers of annotations – pos tags, treebanking, propbanking, UMLS entities (Diseases/disorders, Signs/Symptoms, Procedures, Anatomical sites, Medications) and modifiers, UMLS relations (locationOf, degreeOf, resultsOf, treats/manages) and modifiers, coreference, template (Clinical Element Model; http://intermountainhealthcare.org/cem) • THYME (Temporal Histories of Your Medical Events) • 500K words of clinical narrative • Layers of annotations – same as MiPACQ and SHARPn + temporal relations (ISO TimeML extensions to the clinical domain)

19. Sample Annotations

20. Presentation Lineup

21. Presentations • Dr. Steven Bethard • Enabling NLP technologies: dependency parsing and dependency-based semantic role labeling • Critical for discovering CEM attributes and populating the CEM template • Dr. Dmitriy Dligach • Focus on discovering two CEM modifiers – body site and severity • Dr. Stephen Wu • Focus on discovering CEM modifiers related to the subject of the clinical event • Dr. Cheryl Clark • Focus on discovering CEM modifiers for negation and uncertainty • Implemented and released in cTAKES • Monday 1-2:30 pm, cTAKES tutorial and demo • Monday 3-5 pm, cTAKES coding sprint

22. SHARPn NLP Investigators (in alpha site order) • Childrens Hospital Boston and HMS (site PI: GuerganaSavova) • Mayo Clinic (Hongfang Liu) • MIT (site PI: Peter Szolovits) • MITRE corporation (site PI: Lynette Hirschman) • Seattle Group Health (site PI: David Carrell) • SUNY Albany (site PI: Ozlem Uzuner) • University of California, San Diego (site PI: Wendy Chapman) • University of Colorado (site PI: Martha Palmer) • University of Utah and Intermountain Healthcare (site PI: Peter Haug)