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ECSTRA-INSERM @ CLEF eHealth2016-task 2: ICD10 Code Extraction from Death Certificates
- Source :
- Conference and Labs of the Evaluation Forum, Conference and Labs of the Evaluation Forum, Sep 2016, Evora, Portugal
- Publication Year :
- 2016
- Publisher :
- HAL CCSD, 2016.
-
Abstract
- International audience; This paper describes the participation of ECSTRA-INSERM team at CLEF eHealth 2016, task 2.C. The task involves extracting ICD10 codes from death certificates, mainly described with short plain texts. We cast the task as a machine learning problem involving the prediction of the ICD10 codes (categorical variable) from the raw text transformed into a bag-of-words matrix. We rely on probabilistic topic models that we evaluate against classical classifiers such as SVM and Naive Bayes. We demonstrate the effectiveness of topic models for this task in terms of prediction accuracy and result interpretation.
- Subjects :
- [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]
[INFO.INFO-TT] Computer Science [cs]/Document and Text Processing
cause of death extraction
text mining
ICD10 code assignment
[STAT.ML] Statistics [stat]/Machine Learning [stat.ML]
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
[INFO.INFO-TT]Computer Science [cs]/Document and Text Processing
topic models
machine learning
[STAT.ML]Statistics [stat]/Machine Learning [stat.ML]
[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]
[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]
natural language processing
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Conference and Labs of the Evaluation Forum, Conference and Labs of the Evaluation Forum, Sep 2016, Evora, Portugal
- Accession number :
- edsair.dedup.wf.001..084f6333f72199d1eba8564df1b3aac4