case_images: PMC4207225_01
case_images: Semantic annotation and indexing of case reports from PubMed.
case_images: bau045f1p.jpg
case_images: PMC4207225_01_bau045f1p.jpg
case_images: bau045-F1
case_images: Using the available abstracts of PubMed (Figure 1), our method extracts the phenotype-relevant snippets of the case reports on CTX.
case_images: PMC4207225_02
case_images: Example of extraction of a snippet of information from an abstract and its subsequent annotation.
case_images: bau045f2p.jpg
case_images: PMC4207225_02_bau045f2p.jpg
case_images: bau045-F2
case_images: Figure 2 shows an example of extracting a relevant snippet from a PubMed abstract.
case_images: PMC4207225_03
case_images: PMC4207225_04
case_images: Venn diagram showing where the two methods overlap.
case_images: bau045f4p.jpg
case_images: PMC4207225_04_bau045f4p.jpg
case_images: bau045-F4
case_images: By applying the automated method to the 223 papers selected by the manual method, only 124 (55%) papers tagged as 'case reports' were selected by our method (Figure 4). Our results shows that using a set of linguistic patterns based on the regularities observed in the expression of patient information in clinical abstracts, we were able to identify 50 more case reports that had not been tagged as such (Figure 4).
case_images: Percentage of papers selected by each method.
case_images: bau045f5p.jpg
case_images: PMC4207225_04_bau045f5p.jpg
case_images: bau045-F5
case_images: Figure 5 shows the percentage of selected papers by each method.   