Presentation given at FARR institute international conference in 2015

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

7. Table analysis overview

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

12. Example of decomposition

13. Example of decomposition

14. Example of decomposition

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

19. nikola.milosevic@manchester.ac.uk