Text Mining for Biology and Biomedicine

Chapter 5: Abbreviations in Biomedical Text

Jeff Chang Hinrich Sch tze

5.1 Introduction

Abbreviations, representing shortened forms of names of concepts, including diseases and genes, are prevalent in the biomedical literature. In the age of high-throughput genomic analyses, the rate at which new molecules are discovered and characterized is increasing, which is reflected in the ever-growing numbers of scientific articles. As a result, the number of abbreviations used in the literature also increases (see Figure 5.1). In the biomedical literature, 64,262 new abbreviations were introduced in 2004, and there is an average of one new abbreviation in every 5 to 10 abstracts [1]


Figure 5.1: The number of new abbreviations and abstracts observed in MEDLINE each year is increasing.

Therefore, it is becoming increasingly difficult for researchers to keep up with known abbreviations. When encountering an unfamiliar abbreviation, one possible solution is to use a dictionary of abbreviations, such as the Dictionary of Medical Acronyms & Abbreviations [2] However, such manual compilations suffer from several problems. First, dictionaries contain from 4,000 to 32,000 abbreviations [3], which is only a fraction of the approximately 800,000 believed to exist [1]. Second, due to the rapid and continuous creation of new abbreviations, "acronym dictionaries are outdated by the time they are published" [4] Finally, dictionaries do not quantify the popularity of an abbreviation, which would be useful to help distinguish among possible different meanings [3].

Often, an abbreviation can be interpreted as several different definitions. For example, ACE can be either angiotensin converting enzyme

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