Automatic ICD-10 classification of cancers from free-text death certificates

International Journal of Medical Informatics

Volumn 84, Issue 11, 2015, Pages 956-965

  Koopman, Bevan ^a   Zuccon, Guido ^b   Nguyen, Anthony ^a   Bergheim, Anton ^c   Grayson, Narelle ^c  

^a CSIRO   (Australia)

^b QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

^c CANCER INSTITUTE NSW   (Australia)

Author keywords

Cancer classification; Death certificates; Machine learning; Natural language processing

Indexed keywords

ARTIFICIAL INTELLIGENCE; AUTOMATION; COMPUTATIONAL LINGUISTICS; DISEASES; LEARNING ALGORITHMS; LEARNING SYSTEMS; NATURAL LANGUAGE PROCESSING SYSTEMS; SUPPORT VECTOR MACHINES; TEXT PROCESSING;

AUTOMATIC CLASSIFICATION SYSTEMS; AUTOMATIC IDENTIFICATION; CANCER CLASSIFICATION; CLASSIFICATION SYSTEM; DEATH CERTIFICATES; NATURAL LANGUAGE PROCESSING; SUPPORT VECTOR MACHINE CLASSIFIERS; TYPE CLASSIFICATIONS;

CLASSIFICATION (OF INFORMATION);

ARTICLE; CANCER CLASSIFICATION; CANCER MORTALITY; CANCER REGISTRY; CAUSE OF DEATH; DEATH CERTIFICATE; ICD-10; MACHINE LEARNING; MEASUREMENT ACCURACY; NATURAL LANGUAGE PROCESSING; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE; SYSTEMATIZED NOMENCLATURE OF MEDICINE; CLASSIFICATION; EPIDEMIOLOGY; HUMAN; INTERNATIONAL CLASSIFICATION OF DISEASES; MORTALITY; NEOPLASM; NEW SOUTH WALES; PROGRAM EVALUATION; REGISTER; STANDARDS;

CAUSE OF DEATH; DEATH CERTIFICATES; HUMANS; INTERNATIONAL CLASSIFICATION OF DISEASES; MACHINE LEARNING; NATURAL LANGUAGE PROCESSING; NEOPLASMS; NEW SOUTH WALES; PROGRAM EVALUATION; REGISTRIES;

EID: 84942553128     PISSN: 13865056     EISSN: 18728243     Source Type: Journal    
DOI: 10.1016/j.ijmedinf.2015.08.004     Document Type: Article

References (18)

1. German R.R., Fink A.K., Heron M., Stewart S.L., Johnson C.J., Finch J.L., Yin D. The accuracy of cancer mortality statistics based on death certificates in the United States. Cancer Epidemiol. 2011, 35(2):126-131.
2. Coleman M., Forman D., Bryant H., Butler J., Rachet B., Maringe C., Nur U., Tracey E., Coory M., Hatcher J., et al. Cancer survival in Australia, Canada, Denmark, Norway, Sweden, and the UK, 1995-2007 (the international cancer benchmarking partnership): an analysis of population-based cancer registry data. Lancet 2011, 377(9760):127-138.
3. Cancer Council Australia Cancer in Australia: Facts and Figures 2014, URL http://www.cancer.org.au/about-cancer/what-is-cancer/facts-and-figures.html (cited 14.1014).
4. World Health Organization Medical Certification of Cause of Death: Instructions for Physicians on Use of International Form of Medical Certificate of Cause of Death 1979, World Health Organization, Geneva. fourth ed.
5. World Health Organization International Statistical Classification of Diseases and Related Health Problems 2004, vol. 1. World Health Organization.
6. Nguyen A., Moore J., Lawley M., Hansen D., Colquist S. Automatic extraction of cancer characteristics from free-text pathology reports for cancer notifications. Health Informatics Conference, vol. 168 2011, 117-124.
7. Nguyen A.N., Lawley M.J., Hansen D.P., Colquist S. A simple pipeline application for identifying and negating snomed clinical terminology in free text. Health Informatics Conference, Canberra, Australia 2009, 188-193.
8. Butt L., Zuccon G., Nguyen A., Bergheim A., Grayson N. Classification of cancer-related death certificates using machine learning. Australas. Med. J. 2013, 6(5):292.
9. Berg J.W. Morphologic classification of human cancer. Cancer Epidemiology and Prevention 1982, 74-89. WB Saunders Co., Eastbourne, UK. D. Schottenfeld, J.F.J. Fraumeni (Eds.).
10. Witten I.H., Frank E. Data Mining: Practical Machine Learning Tools and Techniques 2005, Morgan Kaufmann.
11. Chai K.E., Anthony S., Coiera E., Magrabi F. Using statistical text classification to identify health information technology incidents. J. Am. Med. Inform. Assoc. 2013, amiajnl-2012.
12. Centers for Disease Control and Prevention Instructions for Classifying the Underlying Cause-of-Death, ICD-10 2014.
13. Nguyen A.N., Lawley M.J., Hansen D.P., Bowman R.V., Clarke B.E., Duhig E.E., Colquist S. Symbolic rule-based classification of lung cancer stages from free-text pathology reports. J. Am. Med. Inform. Assoc. 2010, 17(4):440-445.
14. Gjerstorff M.L. The Danish cancer registry. Scand. J. Public Health 2011, 39(7 Suppl.):42-45.
15. Spasić I., Livsey J., Keane J.A., Nenadić G. Text mining of cancer-related information: review of current status and future directions. Int. J. Med. Inform. 2014, 83(9):605-623.
16. Riedl B., Than N., Hogarth M. Using the UMLS and simple statistical methods to semantically categorize causes of death on death certificates. AMIA Annual Symposium Proceedings, vol. 2010 2010, 677. American Medical Informatics Association.
17. Davis K., Staes C., Duncan J., Igo S., Facelli J.C. Identification of pneumonia and influenza deaths using the death certificate pipeline. BMC Med. Inform. Decis. Mak. 2012, 12(1):37.
18. Shah A.D., Martinez C., Hemingway H. The freetext matching algorithm: a computer program to extract diagnoses and causes of death from unstructured text in electronic health records. BMC Med. Inform. Decis. Mak. 2012, 12(1):88.