Text mining, machine learning, NLP and all that (in 10 minutes)

1.540 visualizaciones

Publicado el

Byron C Wallace, from #CochraneTech Symposium, Québec 2013

Publicado en: Tecnología, Salud y medicina
0 comentarios
1 recomendación
Estadísticas
Notas
  • Sé el primero en comentar

Sin descargas
Visualizaciones
Visualizaciones totales
1.540
En SlideShare
0
De insertados
0
Número de insertados
5
Acciones
Compartido
0
Descargas
25
Comentarios
0
Recomendaciones
1
Insertados 0
No insertados

No hay notas en la diapositiva.

Text mining, machine learning, NLP and all that (in 10 minutes)

  1. 1. text mining, machine learning, NLP and all that (in 10 minutes) Byron C Wallace Brown Center for Evidence Based Medicine #CochraneTech
  2. 2. why do we need this stuff? [Bastian et al, PLoS Medicine 2010]
  3. 3. why do we need this stuff? [Bastian et al, PLoS Medicine 2010]
  4. 4. PubMed growth [http://altmetrics.org/wp-content/uploads/2010/10/medline-articles-by-year-lg.png]
  5. 5. PubMed ? 2 search database 1 formulate question, protocol & query 4 extract data treatment outcome ba c d 3 screen retrieved citations Studies AIMS1988 ASSET1988 Aber1976 Amery1969 Anderson1983 Bassand1986 Bett1973 Bossaert1987 Brunelli1988 Buchalter1987 Croydon1987 Dewar1963 Durand1987 ECSG−11979 ECSG−21988 EWP1971 Fletcher1959 GISSI1986 Gormsen1973 Guerci1987 Heikinheim1971 ISAM1986 ISISPilot1987 ISIS−21988 Ikram1986 Julian1987 Khaja1983 Leiboff1984 Maublant1988 Meinertz1988 NHFAustra1988 Olson1986 Raizner1985 Rentrop1984 Sainsous1986 Schreiber1986 Simoons1985 TICO1988 Topol1987 WWICSK1983 WWIVSK1988 White1987 Overall (I^2=19% , P=0.147) 0 0.01 0.02 0.04 0.08 0.190.270.38 0.76 1.91 3.82 7.65 18.26 OddsRatio(logscale) 5 synthesize extracted data what can we automate
  6. 6. PubMed ? 2 search database 1 formulate question, protocol & query 4 extract data treatment outcome ba c d 3 screen retrieved citations Studies AIMS1988 ASSET1988 Aber1976 Amery1969 Anderson1983 Bassand1986 Bett1973 Bossaert1987 Brunelli1988 Buchalter1987 Croydon1987 Dewar1963 Durand1987 ECSG−11979 ECSG−21988 EWP1971 Fletcher1959 GISSI1986 Gormsen1973 Guerci1987 Heikinheim1971 ISAM1986 ISISPilot1987 ISIS−21988 Ikram1986 Julian1987 Khaja1983 Leiboff1984 Maublant1988 Meinertz1988 NHFAustra1988 Olson1986 Raizner1985 Rentrop1984 Sainsous1986 Schreiber1986 Simoons1985 TICO1988 Topol1987 WWICSK1983 WWIVSK1988 White1987 Overall (I^2=19% , P=0.147) 0 0.01 0.02 0.04 0.08 0.190.270.38 0.76 1.91 3.82 7.65 18.26 OddsRatio(logscale) 5 synthesize extracted data what can we automate
  7. 7. what can we automate?
  8. 8. learner unlabeled data U expert labeled data L predictive model abstracts from PubMed search doctor conducting review manually screened abstracts SVM how does this work?
  9. 9. SVMs o x o o o o o o o o x x x x x x xx x xx x support vectors margino
  10. 10. bag of words1.2 Supervised M achine Learn I am a Nigerian prince writing to you about an inheritance... ... dinner about prince call ... work nigerian yesterday office inheritance ... ... 0 1 1 0 ... 0 1 0 0 1 ... Figure 1.4: The (binary) Bag-of-Words (BoW) representation.
  11. 11. special considerations for the case of systematic reviews • class imbalance – far fewer relevant than irrelevant abstracts – asymmetric costs sensitivity more important than specificity • reviewer time is scarce and expensive – better models, fewer labels: active learning and dual supervision
  12. 12. how do we do? “Towards Modernizing the Systematic Review Pipeline: Efficient Updating via Data Mining” Genetics in Medicine 2012
  13. 13. PubMed ? 2 search database 1 formulate question, protocol & query 4 extract data treatment outcome ba c d 3 screen retrieved citations Studies AIMS1988 ASSET1988 Aber1976 Amery1969 Anderson1983 Bassand1986 Bett1973 Bossaert1987 Brunelli1988 Buchalter1987 Croydon1987 Dewar1963 Durand1987 ECSG−11979 ECSG−21988 EWP1971 Fletcher1959 GISSI1986 Gormsen1973 Guerci1987 Heikinheim1971 ISAM1986 ISISPilot1987 ISIS−21988 Ikram1986 Julian1987 Khaja1983 Leiboff1984 Maublant1988 Meinertz1988 NHFAustra1988 Olson1986 Raizner1985 Rentrop1984 Sainsous1986 Schreiber1986 Simoons1985 TICO1988 Topol1987 WWICSK1983 WWIVSK1988 White1987 Overall (I^2=19% , P=0.147) 0 0.01 0.02 0.04 0.08 0.190.270.38 0.76 1.91 3.82 7.65 18.26 OddsRatio(logscale) 5 synthesize extracted data beyond citation screening
  14. 14. PubMed ? 2 search database 1 formulate question, protocol & query 4 extract data treatment outcome ba c d 3 screen retrieved citations Studies AIMS1988 ASSET1988 Aber1976 Amery1969 Anderson1983 Bassand1986 Bett1973 Bossaert1987 Brunelli1988 Buchalter1987 Croydon1987 Dewar1963 Durand1987 ECSG−11979 ECSG−21988 EWP1971 Fletcher1959 GISSI1986 Gormsen1973 Guerci1987 Heikinheim1971 ISAM1986 ISISPilot1987 ISIS−21988 Ikram1986 Julian1987 Khaja1983 Leiboff1984 Maublant1988 Meinertz1988 NHFAustra1988 Olson1986 Raizner1985 Rentrop1984 Sainsous1986 Schreiber1986 Simoons1985 TICO1988 Topol1987 WWICSK1983 WWIVSK1988 White1987 Overall (I^2=19% , P=0.147) 0 0.01 0.02 0.04 0.08 0.190.270.38 0.76 1.91 3.82 7.65 18.26 OddsRatio(logscale) 5 synthesize extracted data beyond citation screening
  15. 15. Questions? byron_wallace@brown.edu http://www.cebm.brown.edu/software www.cebm.brown.edu/byron

×