Aude Robert


A Dataset for ICD-10 Coding of Death Certificates: Creation and Usage
Thomas Lavergne | Aurélie Névéol | Aude Robert | Cyril Grouin | Grégoire Rey | Pierre Zweigenbaum
Proceedings of the Fifth Workshop on Building and Evaluating Resources for Biomedical Text Mining (BioTxtM2016)

Very few datasets have been released for the evaluation of diagnosis coding with the International Classification of Diseases, and only one so far in a language other than English. This paper describes a large-scale dataset prepared from French death certificates, and the problems which needed to be solved to turn it into a dataset suitable for the application of machine learning and natural language processing methods of ICD-10 coding. The dataset includes the free-text statements written by medical doctors, the associated meta-data, the human coder-assigned codes for each statement, as well as the statement segments which supported the coder’s decision for each code. The dataset comprises 93,694 death certificates totalling 276,103 statements and 377,677 ICD-10 code assignments (3,457 unique codes). It was made available for an international automated coding shared task, which attracted five participating teams. An extended version of the dataset will be used in a new edition of the shared task.

Replicability of Research in Biomedical Natural Language Processing: a pilot evaluation for a coding task
Aurélie Névéol | Kevin Cohen | Cyril Grouin | Aude Robert
Proceedings of the Seventh International Workshop on Health Text Mining and Information Analysis