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.