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Explorarea tendinţelor temporo-spaţiale ale
cheilor de căutare pentru cercetarea biomedicală folosind baza de
date Medline/PubMed.
Alexandru Dan Corlan,
Revista de Politica Ştiinţei şi Scientometrie 1(4):281-292, 2012
ABSTRACT
We announce a new version of the online data mining
tool 'Medline Trend' (http://dan.corlan.net/medline-trend.html) that
extends the yearly trends with spatial (geographic) statistics. In a
nutshell, the user introduces a normal query, such as the name of a
disease, and obtains counts of PubMed entries (papers) for each
country and time interval. The country of origin is detected from the
address (AD) field. In contrast with the date of publication, the
presence and significance of at least one recognisable country name in
the address field is more variable and the address field itself seems
to only have been introduced in Medline about 20 years ago. For
example, at the date of writing, in the 2008–2012 interval, only about
3.34 million entries out of 4.052 million had a recognisable country
name. For earlier years, the rate is even lower. In this paper, we
propose a number of indices that are not directly influenced by the
address field variability. They are based on the relative value of one
spatial index to others, computed for the same time interval or
region. The annualised rate of change of the number of papers for a
keyowrd and region over a time interval is the compund anual rate of
change of the number of entries fulfilling the search criteria fitted
to the actually observed counts. The relative interest is the
proportion of entries on a topic (such as ‘tuberculosis’) in a
geographical region and over a specified time interval compared to all
entries originating from that region during the same time interval. We
found that, at least for tuberculosis, there is a strong and
consistent log-log relationship between the relative interest and the
prevalence of the disease in that area and period. The interest–size
corelation index is the Spearman (ρ) correlation between the absolute
output of a country and the relative interest for a given keyword. It
might grossly indicate whether a topic attracts more interest in
countries with more rather than less developed scientific systems. It
is for example 0.26 for ‘echocardiography’, -0.48 for ‘tuberculosis’,
0.72 for ‘stem cell’, 0.15 for ‘diabetes’, -0.06 for
‘malaria’. Spatiotemporal trends might sometimes provide insightful
clues into the quantitative mechanisms that lead to adoption of a
particular research thematic, but their application requires attension
to numerous limitations and caveats, in addition to the usual
limitations of paper count statistics.
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