Related Experiment Video
Updated: Aug 16, 2026
A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Refinement of an automatic method for indexing medical literature--a preliminary study
Michel Joubert1, Anne-Laure Peretti, Joanny Gouvernet
1LERTIM, Faculté de Médecine, Université de la Méditerranée, Marseille, France.
Objectives:
to rank according to their significance MeSH terms automatically extracted from Internet sites in the framework of a French project, VUMeF, a contribution to the NLM' UMLS project.
Material And Methods:
scores are affected to key-words of a given document on the basis of the Semantic Network of the UMLS and frequencies of co-occurring major terms in the Medline literature. If N is the number of major terms of a document, and n is the number of major terms retrieved in the N first terms ranked in descending order according to their scores, the measure of the achievement of the method is n/N.
Results:
a set of 1444 randomized documents have been extracted from Medline. For each document we computed the retrieved major terms among the first N terms with two methods: a statistical method using only frequencies given by co-occurrences, and our method that uses furthermore the UMLS semantic network. In 34% of cases corresponding to documents indexed by about 16 key-words, about 3 major terms among them, our method produces a better precision (7%) than the statistical method.
Discussion:
the rough calculation of the proportion of retrieved major terms should be enhanced by the use of a probability law allowing to enlarge the list of terms to select taking into account both the number of major terms and the total number of key-words used to index each document.
