Distribution of information in biomedical abstracts and full-text publications. Schuemie, M., J., Weeber, M., Schijvenaars, B., J., A., Van Mulligen, E., M., Van Der Eijk, C., C., Jelier, R., Mons, B., & Kors, J., A. Bioinformatics, 20(16):2597-2604, 2004. ![Distribution of information in biomedical abstracts and full-text publications. [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website abstract bibtex MOTIVATION: Full-text documents potentially hold more information than their abstracts, but require more resources for processing. We investigated the added value of full text over abstracts in terms of information content and occurrences of gene symbol-gene name combinations that can resolve gene-symbol ambiguity. RESULTS: We analyzed a set of 3902 biomedical full-text articles. Different keyword measures indicate that information density is highest in abstracts, but that the information coverage in full texts is much greater than in abstracts. Analysis of five different standard sections of articles shows that the highest information coverage is located in the results section. Still, 30-40% of the information mentioned in each section is unique to that section. Only 30% of the gene symbols in the abstract are accompanied by their corresponding names, and a further 8% of the gene names are found in the full text. In the full text, only 18% of the gene symbols are accompanied by their gene names.
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title = {Distribution of information in biomedical abstracts and full-text publications.},
type = {article},
year = {2004},
identifiers = {[object Object]},
pages = {2597-2604},
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websites = {http://www.ncbi.nlm.nih.gov/pubmed/15130936},
institution = {Department of Medical Informatics, Erasmus University Medical Center Rotterdam, P.O. Box 1738, 3000 DR, Rotterdam, The Netherlands. m.schuemie@erasmusmc.nl},
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abstract = {MOTIVATION: Full-text documents potentially hold more information than their abstracts, but require more resources for processing. We investigated the added value of full text over abstracts in terms of information content and occurrences of gene symbol-gene name combinations that can resolve gene-symbol ambiguity. RESULTS: We analyzed a set of 3902 biomedical full-text articles. Different keyword measures indicate that information density is highest in abstracts, but that the information coverage in full texts is much greater than in abstracts. Analysis of five different standard sections of articles shows that the highest information coverage is located in the results section. Still, 30-40% of the information mentioned in each section is unique to that section. Only 30% of the gene symbols in the abstract are accompanied by their corresponding names, and a further 8% of the gene names are found in the full text. In the full text, only 18% of the gene symbols are accompanied by their gene names.},
bibtype = {article},
author = {Schuemie, M J and Weeber, M and Schijvenaars, B J A and Van Mulligen, E M and Van Der Eijk, C C and Jelier, R and Mons, B and Kors, J A},
journal = {Bioinformatics},
number = {16}
}
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