TY - JOUR
T1 - Mining of clinical and biomedical text and data
T2 - Editorial of the special issue
AU - Karsten, Helena
AU - Suominen, Hanna
PY - 2009/12
Y1 - 2009/12
N2 - To cope with the amounts of documentation in health care and bio-medical research, the traditional intermediaries used by practitioners include, for example, summaries, code lists, and rulebooks. The new intermediaries enabled by text and data mining may encompass, for example, code suggestions assigned by text classification tools, rankings produced by information retrieval tools, pre-completed forms filled by information extraction tools, as well as structured free-text notes generated by topic segmentation and labelling tools. Under time constraints, they can help focus on essential items in large sets of data and text. This Special Issue is about these intermediaries.
AB - To cope with the amounts of documentation in health care and bio-medical research, the traditional intermediaries used by practitioners include, for example, summaries, code lists, and rulebooks. The new intermediaries enabled by text and data mining may encompass, for example, code suggestions assigned by text classification tools, rankings produced by information retrieval tools, pre-completed forms filled by information extraction tools, as well as structured free-text notes generated by topic segmentation and labelling tools. Under time constraints, they can help focus on essential items in large sets of data and text. This Special Issue is about these intermediaries.
KW - Text mining
KW - Clinical data
KW - Biomedical data
UR - http://www.scopus.com/inward/record.url?scp=71649097096&partnerID=8YFLogxK
U2 - 10.1016/j.ijmedinf.2009.09.006
DO - 10.1016/j.ijmedinf.2009.09.006
M3 - Editorial
C2 - 19875332
AN - SCOPUS:71649097096
SN - 1386-5056
VL - 78
SP - 786
EP - 787
JO - International Journal of Medical Informatics
JF - International Journal of Medical Informatics
IS - 12
ER -