Supporting clinical trial data curation and integration with table mining
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Presentation given at FARR institute international conference in 2015
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Supporting clinical trial data curation and integration with table mining
- 1. Supporting clinical trial data curation and integration with table mining Nikola Milosevic1, Cassie Gregson3, Robert Hernandez3, Goran Nenadic1,2 1School of Computer Science, University of Manchester 2 The Farr Institute @HeRC 3AstraZeneca
- 2. Clinical trial publications • Around 800 000 clinical trials in PubMed • Difficult to digest/search • Text mining approaches • But tables and figures are often not processed
- 3. Tables in publications • Present factual information • Usually: • Experimental settings (i.e. demographics) • Findings and results (e.g. DDI, side effects, adverse events…) • Background information (previous research, datasets, etc.) • Examples • Important information about trials
- 4. Extraction and curation of table data
- 5. Challenges • Complex structure • Table dimensionality (1, 2, multi-dimensional) • Visual relationships • Dense content • Ambiguous short text • Lack of context • Acronyms and abbreviations • Incomplete information
- 8. Table types (1) • 4 types: list, matrix, super-row and multi-tables • List table:
- 9. Table types (2) • Matrix table
- 10. Table types (3) • Super-row table
- 11. Table types (4) • Multi-table
- 15. Results
- 16. Next steps • Add semantic annotations • Link patterns in data cells with its meaning • Build/Expand knowledge bases • Relate to existing knowledge on the semantic web
- 17. Annotation schema • Meta-data • Paper (name, abstract, authors, publisher) • Authors (names, emails, affiliations) • Table (caption, footers) • Cells (content, role) • Inter-cell relationships • Semantics (links to ontologies, dictionaries, knowledge bases)
- 18. Summary • Tables contain valuable information such as settings or results • System for extraction and curation of table data • Decomposition and annotation of the tables • Accuracy of 85% • Semantic analysis and information extraction