Analysis of the adjectives of a medical corpus by means of automatic language processing
2000, Vol. V-2, pp. 151-160
Divergent descriptions of histopathologic images induce inter- and intra-observer variability in diagnosis based on the observation of breast tumours images. The lack of reproducibility in identifying specific morphological features is partly due to varying levels of expertise among pathologists and to differences in subjective analysis and comprehension of pathological images. As linguists and developers of Natural Language Processing (NLP) systems, we started a collaboration with the Medical Informatics Department at the Broussais Hospital in order to explore a new way for corpus-based medical glossary acquisition. We focused our analysis on adjectives because they are the main linguistic category involved in the evaluation process. The first results of this study show the relevance of a corpus-based approach to cope with the "subjective" interpretations given by pathologists when they analyse microscopic images.