SWIFT-Review: A text-mining workbench for systematic review

Systematic Reviews

Volumn 5, Issue 1, 2016, Pages

  Howard, Brian E ^a   Phillips, Jason ^a   Miller, Kyle ^a   Tandon, Arpit ^a   Mav, Deepak ^a   Shah, Mihir R ^a   Holmgren, Stephanie ^b   Pelch, Katherine E ^b   Walker, Vickie ^b   Rooney, Andrew A ^b   Macleod, Malcolm ^c   Shah, Ruchir R ^a   Thayer, Kristina ^b  

^a National Institute of Environmental Health Sciences   (United States)

^b NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES   (United States)

^c UNIVERSITY OF EDINBURGH   (United Kingdom)

Author keywords

Literature prioritization; Scoping reports; Software; SWIFT Review; Systematic review

Indexed keywords

ALGORITHM; ARTICLE; COMPUTER PROGRAM; DATA MINING; HUMAN; MEDICAL RESEARCH; NONHUMAN; OUTCOME ASSESSMENT; PRIORITY JOURNAL; PUBLICATION; SCIENTIFIC LITERATURE; SYSTEMATIC REVIEW; TOXICITY; FACTUAL DATABASE; INFORMATION RETRIEVAL; LITERATURE; MACHINE LEARNING; SOFTWARE; STATISTICAL MODEL;

ALGORITHMS; DATA MINING; DATABASES, FACTUAL; HUMANS; INFORMATION STORAGE AND RETRIEVAL; LINEAR MODELS; MACHINE LEARNING; REVIEW LITERATURE AS TOPIC; SOFTWARE;

EID: 84969524607     PISSN: None     EISSN: 20464053     Source Type: Journal    
DOI: 10.1186/s13643-016-0263-z     Document Type: Article

References (30)

1. Bastian H, Glasziou P, Chalmers I. Seventy-five trials and eleven systematic reviews a day: how will we ever keep up? PLoS Med. 2010;7(9):e1000326.
2. Ganann R, Ciliska D, Thomas H. Expediting systematic reviews: methods and implications of rapid reviews. Implement Sci. 2010;5(1):56.
3. Jonnalagadda SR, Goyal P, Huffman MD. Automating data extraction in systematic reviews: a systematic review. Syst Rev. 2015;4(1):78.
4. O'Mara-Eves A, Thomas J, McNaught J, Miwa M, Ananiadou S. Using text mining for study identification in systematic reviews: a systematic review of current approaches. Syst Rev. 2015;4(1):5.
5. Colquhoun HL, Levac D, O'Brien KK, Straus S, Tricco AC, Perrier L, Kastner M, Moher D. Scoping reviews: time for clarity in definition, methods, and reporting. J Clin Epidemiol. 2014;67(12):1291-4.
6. Cohen AM, Hersh WR, Peterson K, Yen PY. Reducing workload in systematic review preparation using automated citation classification. J Am Med Inform Assoc. 2006;13:206-19.
7. Robertson SE, Porter MF. New Models in Probabilistic Information Retrieval. Issue 5587 of British Library research & development report. London: Publisher Computer Laboratory, University of Cambridge; 1980. p. 123.
8. Robertson S. Understanding inverse document frequency: on theoretical arguments for IDF. J Doc. 2004;60(5):503-20.
9. Blei DM, Ng AY, Jordan MI. Latent Dirichlet allocation. J Mach Learn Res. 2003;3:993-1022.
10. Blei DM. Probabilistic topic models. Commun ACM. 2012;55(4):77-84.
11. McCallum A. MALLET: a machine learning for language toolkit. 2002 [Online]. Available: http://mallet.cs.umass.edu. [Accessed: 27 July 2015].
12. Byrd RH, Lu P, Nocedal J, Zhu C. A limited memory algorithm for bound constrained optimization. SIAM J Sci Comput. 1995;16(5):1190-208.
13. Hooijmans CR, Tillema A, Leenaars M, Ritskes-Hoitinga M. Enhancing search efficiency by means of a search filter for finding all studies on animal experimentation in PubMed. Lab Anim. 2010;44(3):170-5.
14. Kavlock RJ, Austin CP, Tice RR. Toxicity testing in the 21st century: implications for human health risk assessment. Risk Anal. 2009;29(4):485-7. discussion 492-7.
15. TM) Data." [Online]. Available: http://www.epa.gov/chemical-research/toxicity-forecaster-toxcasttm-data. [Accessed: 09 Feb 2016].
16. (NLM) National Library of Medicine. ChemIDplus Lite-chemical information with searchable synonyms, structures, and formulas. 2015 [Online]. Available: http://chem.sis.nlm.nih.gov/chemidplus/chemidlite.jsp. [Accessed: 03 Dec 2015].
17. SIL. English wordlists. 2015 [Online]. Available: http://www-01.sil.org/linguistics/wordlists/english/. [Accessed: 01 Jan 2015].
18. (WHO/UNEP) World Health Organization/United Nations Environment Programme. WHO | State of the science of endocrine disrupting chemicals - 2012. 2012 [Online]. Available: http://www.who.int/ceh/publications/endocrine/en/. [Accessed: 26 Jan 2015].
19. (NIEHS) National Institute of Environmental Sciences. Endocrine disruptor factsheet. 2010 [Online]. Available: http://www.niehs.nih.gov/health/materials/endocrine_disruptors_508.pdf. [Accessed: 25 Jan 2015].
20. "State of the Science Evaluation for Transgenerational Inheritance of Health Effects - NTP." [Online]. Available: http://ntp.niehs.nih.gov/pubhealth/hat/noms/trans/index.html. [Accessed: 09 Feb 2016].
21. Bekhuis T, Tseytlin E, Mitchell KJ, Demner-Fushman D. Feature engineering and a proposed decision-support system for systematic reviewers of medical evidence. PLoS One. 2014;9(1):e86277.
22. Thomas J, O'Mara A. How can we find relevant research more quickly? In NCRM MethodsNews. UK:NCRM; 2011. p.3.
23. Wallace BC, Dahabreh IJ, Moran KH, Brodley CE, Trikalinos TA. Active literature discovery for scoping evidence reviews. In: 1th ACM SIGKDD Conference onf Knowledge Discovery and Data Mining (KDD). 2013.
24. Shemilt I, Simon A, Hollands G, Marteau T, Ogilvie D, O'Mara-Eves A, et al. Pinpointing needles ingiant haystacks: use of text mining to reduce impractical screening workload in extremely large scoping reviews. Res Synth Methods. 2014;5(1):31-49.
25. Miwa M, Thomas J, O'Mara-Eves A, Ananiadou S. Reducing systematic review workload through certainty-based screening. J Biomed Inform. 2014;51:242-53.
26. Jonnalagadda S, Petitti D. A new iterative method to reduce workload in the systematic review process. Int J Comput Biol Drug Des. 2013;6:5-17.
27. Wallace B, Small K, Brodley C, Trikalinos T. Active learning for biomedical citation screening. Washington USA: KDD 2010; 2010.
28. Frunza O, Inkpen D, Matwin S. Building systematic reviews using automatic text classification techniques. 2010. p. 303-11.
29. Cohen AM. Performance of support-vector-machine-based classification on 15 systematic review topics evaluated with the WSS@95 measure. J Am Med Inform Assoc. 2011;18(1):104. author reply 104-105.
30. Cohen A. Optimizing feature representation for automated systematic review work prioritization. AMIA Annu Symp Proc 2008. 2008; 121-5. http://www.ncbi.nlm.nih.gov/pubmed/18998798.