In this paper, we describe the approach and results for our participation in the task 1 (multilingual information extraction) of the CLEF eHealth 2018 challenge. We addressed the task of automatically assigning ICD-10 codes to French death certificates. We used a dictionary-based approach using materials provided by the task organizers. The terms of the ICD-10 terminology were normalized, tokenized and stored in a tree data structure. The Levenshtein distance was used to detect typos. Frequent abbreviations were detected by manually creating a small set of them. Our system achieved an F-score of 0.786 (precision: 0.794, recall: 0.779). These scores were substantially higher than the average score of the systems that participated in the challenge.
@article{arxiv.1807.03674,
title = {IAM at CLEF eHealth 2018: Concept Annotation and Coding in French Death Certificates},
author = {Sébastien Cossin and Vianney Jouhet and Fleur Mougin and Gayo Diallo and Frantz Thiessard},
journal= {arXiv preprint arXiv:1807.03674},
year = {2018}
}