Trends in Fetal Medicine: A 10-Year Bibliometric Analysis of Prenatal Diagnosis

Abstract

The objective is to automatically identify trends in Fetal Medicine over the past 10 years through a bibliometric analysis of articles published in Prenatal Diagnosis, using text mining techniques. We processed 2,423 full-text articles published in Prenatal Diagnosis between 2006 and 2015. We extracted salient terms, calculated their frequencies over time, and established evolution profiles for terms, from which we derived falling, stable, and rising trends. We identified 618 terms with a falling trend, 2,142 stable terms, and 839 terms with a rising trend. Terms with increasing frequencies include those related to statistics and medical study design. The most recent of these terms reflect the new opportunities of next-generation sequencing. Many terms related to cytogenetics exhibit a falling trend. A bibliometric analysis based on text mining effectively supports identification of trends over time. This scalable approach is complementary to analyses based on metadata or expert opinion.

Keywords: Bibliometrics; Prenatal Diagnosis.

Figure 1

Term extraction strategy applied to the 2,423 articles from Prenatal Diagnosis (2006–2015). Counts represent numbers of distinct terms (N-grams).

Figure 2

Distribution of terms according to the year in which their cumulative frequency reaches 50% of their total document frequency.

Figure 3

Evolution of term frequency (coloured lines) over time for the top 30 terms exhibiting a falling trend (a), a stable trend (b) and a rising trend (c). (The font size in the term cloud is proportional to term frequency.)