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Related Concept Videos

Rules for Significant Figures01:44

Rules for Significant Figures

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In any measurement, the precision of the measuring tool is an essential factor. An ordinary ruler, for example, can measure length to the closest millimeter; a caliper, on the other hand, can measure length to the nearest 0.01 mm. As a result, the caliper is a more precise measurement tool because it can measure extremely minute changes in length. The measurements will be more accurate if the measuring tool is more precise.
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All the digits in a measurement, including the uncertain last digit, are called significant figures or significant digits. Note that zero may be a measured value; for example, if a scale that shows weight to the nearest pound reads “140,” then the 1 (hundreds), 4 (tens), and 0 (ones) are all significant (measured) values.
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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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Figure and caption extraction from biomedical documents.

Pengyuan Li1, Xiangying Jiang1, Hagit Shatkay1

  • 1Department of Computer and Information Sciences, University of Delaware, Newark, DE, USA.

Bioinformatics (Oxford, England)
|April 6, 2019
PubMed
Summary
This summary is machine-generated.

We developed PDFigCapX, a novel system for extracting figures and captions from biomedical documents. This tool significantly improves the accuracy of figure-caption pair extraction, addressing a critical gap in scientific literature mining.

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Area of Science:

  • Biomedical Informatics
  • Document Analysis
  • Scientific Publishing

Background:

  • Figures and captions are crucial for understanding biomedical documents.
  • Extracting figures and captions from PDFs is challenging due to complex document structures.
  • Existing PDF parsing tools often misidentify figures and captions in scientific publications.

Purpose of the Study:

  • To introduce an effective system for extracting figures and captions from biomedical publications.
  • To address the limitations of current methods in figure and caption extraction.
  • To facilitate knowledge mining from biomedical literature by providing accurate figure-caption pairs.

Main Methods:

  • Developed PDFigCapX, a system that separates text and graphical content.
  • Utilized layout information to detect and extract figures and captions.
  • Generated output files containing figures and their associated captions.

Main Results:

  • PDFigCapX demonstrated significant performance improvements compared to state-of-the-art systems.
  • The system was tested on computer science and biomedical datasets, showing effectiveness and robustness.
  • Achieved accurate extraction of figures and captions, including figure-caption pairs.

Conclusions:

  • PDFigCapX offers a robust solution for figure and caption extraction in biomedical documents.
  • The system enhances the ability to mine knowledge from scientific publications.
  • Public availability of the system and datasets promotes further research in this area.