| Original language | English |
|---|---|
| Pages (from-to) | 127-130 |
| Number of pages | 4 |
| Journal | Artificial Intelligence in Medicine |
| Volume | 61 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2014 |
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In: Artificial Intelligence in Medicine, Vol. 61, No. 3, 2014, p. 127-130.
Research output: Contribution to journal › Editorial
TY - JOUR
T1 - Text mining and information analysis of health documents
AU - Suominen, Hanna
N1 - Funding Information: NICTA is funded by the Australian Government through the Department of Communications and the Australian Research Council through the ICT Centre of Excellence Program. NICTA is also funded and supported by the Australian Capital Territory, the New South Wales, Queensland and Victorian Governments, the Australian National University, the University of New South Wales, the University of Melbourne, the University of Queensland, the University of Sydney, Griffith University, Queensland University of Technology, Monash University and other university partners. Funding Information: The CLEF initiative is an activity of the Participative Research labOratory for Multimedia and Multilingual Information Systems Evaluation Network of Excellence (PROMISE), funded by the European Commission 7th Framework Programme. Its main mission is to promote research, innovation, and development of information access systems with an emphasis on multilingual and multimodal information with various levels of structure. Since 2000, it has played a leading role internationally in stimulating investigation and research in a wide range of key areas related to information access. Each year, it organizes a wider peer-reviewed conference together with more specific workshops and evaluation labs (a.k.a. shared tasks, challenges, hackathons, or competitions where all participants’ goal is to solve the same problem, typically using the same dataset).
PY - 2014
Y1 - 2014
KW - Text mining
KW - Data Mining/methods
KW - Semantics
KW - Humans
KW - Natural Language Processing
KW - Programming Languages
KW - Electronic Health Records
UR - https://www.scopus.com/pages/publications/84904329414
UR - http://www.mendeley.com/research/text-mining-information-analysis-health-documents
U2 - 10.1016/j.artmed.2014.06.001
DO - 10.1016/j.artmed.2014.06.001
M3 - Editorial
C2 - 24998391
AN - SCOPUS:84904329414
SN - 0933-3657
VL - 61
SP - 127
EP - 130
JO - Artificial Intelligence in Medicine
JF - Artificial Intelligence in Medicine
IS - 3
ER -