Text mining for lung cancer cases over large patient admission data

CEUR Workshop Proceedings

Volumn 1149, Issue , 2014, Pages 24-25

  Martinez, David ^a,e   Cavedon, Lawrence ^a,b,e   Alam, Zaf ^c   Bain, Christopher ^c,d   Verspoor, Karin ^a,e  

^a UNIVERSITY OF MELBOURNE   (Australia)

^b RMIT UNIVERSITY   (Australia)

^c Alfred Health ^*  (Australia)

^d MONASH UNIVERSITY   (Australia)

^e CSIRO   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

ABSTRACTING; ARTIFICIAL INTELLIGENCE; BIOLOGICAL ORGANS; DATA MINING; DISEASES; LEARNING SYSTEMS;

KEY WORD MATCHING; LUNG CANCER; PATIENT ADMISSIONS; TEXT MINING; TEXTUAL CONTENT;

BIG DATA;

EID: 84927130175     PISSN: 16130073     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (4)

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2. M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, I. H. Witten. The WEKA Data Mining Software: An Update. SIGKDD Explorations, 2009, Volume 11, Issue 1.
3. D. Martinez, H. Suominen, M. Ananda-Rajah, L. Cavedon, Biosurveillance for Invasive Fungal Infections via text mining, CLEF Wshop on Cross-Language Eval of Methods, Applications, Resources for eHealth Document Analysis, Rome 2012.
4. M. Hall. Correlation-based Feature Subset Selection for Machine Learning. PhD thesis, Dept. Comp. Sci., U. Waikato, 1999.