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Extracting cancer mortality statistics from death certificates: A hybrid machine learning and rule-based approach for common and rare cancers.

, , , , and . Artificial Intelligence in Medicine, (2018)

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Exploiting SNOMED CT Concepts & Relationships for Clinical Information Retrieval: Australian e-Health Research Centre and Queensland University of Technology at the TREC 2012 Medical Track., , , , , and . TREC, Special Publication 500-298, National Institute of Standards and Technology (NIST), (2012)Progressive coding in JPEG2000 - improving content recognition performance using ROIs and importance maps., , , and . EUSIPCO, page 1-4. IEEE, (2002)Factors Influencing Robustness and Effectiveness of Conditional Random Fields in Active Learning Frameworks., , , and . AusDM, volume 158 of CRPIT, page 69-78. Australian Computer Society, (2014)CADEminer: A System for Mining Consumer Reports on Adverse Drug Side Effects., , and . ESAIR@CIKM, page 47-50. ACM, (2015)Automatic classification of diseases from free-text death certificates for real-time surveillance., , , , , , , , and . BMC Med. Inf. & Decision Making, (2015)Transferability of artificial neural networks for clinical document classification across hospitals: A case study on abnormality detection from radiology reports., , , and . Journal of Biomedical Informatics, (2018)Retrieval of Health Advice on the Web AEHRC at ShARe/CLEF eHealth Evaluation Lab Task 3., , and . CLEF (Working Notes), volume 1179 of CEUR Workshop Proceedings, CEUR-WS.org, (2013)Extracting Cancer Mortality Statistics from Free-text Death Certificates: A View from the Trenches., , , , and . ADCS, page 6:1-6:4. ACM, (2018)Clinical Document Classification Using Labeled and Unlabeled Data Across Hospitals., , , and . AMIA, AMIA, (2018)Assuring Authenticity of Digital Mammograms by Image Watermarking., , , , and . Digital Mammography / IWDM, volume 5116 of Lecture Notes in Computer Science, page 204-211. Springer, (2008)