International audienceThis 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
Objectives Widespread implementation of electronic databases has improved the accessibility of plain...
International audienceBACKGROUND: Mortality surveillance is of fundamental importance to public heal...
Objective Death certificates are an invaluable source of cancer mortality statistics. However, this ...
International audienceThis paper describes the participation of ECSTRA-INSERM team at CLEF eHealth 2...
This paper describes the participation of the KFU team in the CLEF eHealth 2017 challenge. Specifica...
A fundamental task for epidemiology, statistics, and health informatics is to associate some standar...
International audienceMining medical data has significantly gained interest in the recent years than...
International audienceThis paper describes the participation of a group of students supervised by tw...
© Springer Nature Switzerland AG 2018. Medical Concept Coding (MCD) is a crucial task in biomedical ...
Medical coding is a process of classify-ing health records according to standard code sets represent...
© 2015 Koopman et al. Background: Death certificates provide an invaluable source for mortality stat...
This study presents a multimodal machine learning model to predict ICD-10 diagnostic codes. We devel...
OBJECTIVES:Widespread implementation of electronic databases has improved the accessibility of plain...
International Classification of Disease (ICD) coding plays a significant role in classify-ing morbid...
Objective Death certificates provide an invaluable source for cancer mortality statistics; however, ...
Objectives Widespread implementation of electronic databases has improved the accessibility of plain...
International audienceBACKGROUND: Mortality surveillance is of fundamental importance to public heal...
Objective Death certificates are an invaluable source of cancer mortality statistics. However, this ...
International audienceThis paper describes the participation of ECSTRA-INSERM team at CLEF eHealth 2...
This paper describes the participation of the KFU team in the CLEF eHealth 2017 challenge. Specifica...
A fundamental task for epidemiology, statistics, and health informatics is to associate some standar...
International audienceMining medical data has significantly gained interest in the recent years than...
International audienceThis paper describes the participation of a group of students supervised by tw...
© Springer Nature Switzerland AG 2018. Medical Concept Coding (MCD) is a crucial task in biomedical ...
Medical coding is a process of classify-ing health records according to standard code sets represent...
© 2015 Koopman et al. Background: Death certificates provide an invaluable source for mortality stat...
This study presents a multimodal machine learning model to predict ICD-10 diagnostic codes. We devel...
OBJECTIVES:Widespread implementation of electronic databases has improved the accessibility of plain...
International Classification of Disease (ICD) coding plays a significant role in classify-ing morbid...
Objective Death certificates provide an invaluable source for cancer mortality statistics; however, ...
Objectives Widespread implementation of electronic databases has improved the accessibility of plain...
International audienceBACKGROUND: Mortality surveillance is of fundamental importance to public heal...
Objective Death certificates are an invaluable source of cancer mortality statistics. However, this ...