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|pdfUrl=https://ceur-ws.org/Vol-1650/smbm16Leser.pdf
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Translational Text Mining
Ulf Leser
Humboldt-Universität zu Berlin
Berlin, Germany
leser@informatik.hu-berlin.de
Abstract ber of the Berlin School for Integrative Oncology
(BSIO).
Text Mining has become an important tool for
many areas of biomedical research. Nevertheless,
its impact actually is still surprisingly small, given
the enormous body of knowledge published every
day and the difficulties of biomedical researchers
to keep an overview of relevant developments even
only in their very specific fields of research. Why
has the usage of some form of semantic search en-
gine or large-scale information extraction pipeline
not yet become the standard procedure for being
up-to-date wrt related work? In this talk, I high-
light some of the key issues text mining faces
when it tries to become ”translational”, i.e., invade
daily biomedical research. Examples are (a) the
misleading focus on ”correct extraction” where it
should be ”correct biological fact”, (b) the wide-
spread negligence of full texts and patents, and
(c) the inaccessibility of typical machine learning
models for end users. Notwithstanding some tech-
nical barriers, I argue that the community must
invest more efforts to move closer to its users to
achieve proper recognition in the field.
Biography
Ulf Leser studied computer science at the Tech-
nische Universitt Mnchen and did his PhD at the
Technische Universitt Berlin. After positions in
research institutes and in the private sector, be be-
came a professor for Knowledge Management in
Bioinformatics at Humboldt-Universitt zu Berlin.
His research focuses on scientific data manage-
ment, statistical Bioinformatics, biomedical text
mining and infrastructures for large-scale Bioin-
formatics analysis, topics he typically approaches
in interdisciplinary projects with biologists and
medical doctors. He is speaker of the gradu-
ate school SOAMED (Service-oriented architec-
tures for medical applications) and a board mem-