Using CISMeF MeSH “Encapsulated” terminology and a categorization algorithm for health resources

Comparing a Rule Based vs. Statistical System for Automatic Categorization of MEDLINE Documents According to Biomedical Specialty

Automatic document categorization is an important research problem in Information Science and Natural Language Processing. Many applications, including Word Sense Disambiguation and Information Retrieval in large collections, can benefit from such categorization. This paper focuses on automatic categorization of documents from the biomedical literature into broad discipline-based categories. Two different systems are described and contrasted: CISMeF, which uses rules based on human indexing of the documents by the Medical Subject Headings(®) (MeSH(®)) controlled vocabulary in order to assign metaterms (MTs), and Journal Descriptor Indexing (JDI) based on human categorization of about 4,000 journals and statistical associations between journal descriptors (JDs) and textwords in the documents. We evaluate and compare the performance of these systems against a gold standard of humanly assigned categories for one hundred MEDLINE documents, using six measures selected from trec_eval. The results show that for five of the measures, performance is comparable, and for one measure, JDI is superior. We conclude that these results favor JDI, given the significantly greater intellectual overhead involved in human indexing and maintaining a rule base for mapping MeSH terms to MTs. We also note a JDI method that associates JDs with MeSH indexing rather than textwords, and it may be worthwhile to investigate whether this JDI method (statistical) and CISMeF (rule based) might be combined and then evaluated showing they are complementary to one another.

[Searching French institutional health information sources: catalogue and index of French-language medical sites (CISMeF)]

The Catalogue and index of French-language medical sites (CISMeF) is a medical portal that provides users with results as pertinent as possible according to their requirements, expectations, and context of use. Indexing and single-term research are based on theMedical subject headings(MeSH) thesaurus. The integration of new medical terminology for indexing the catalogue's resources is intended to minimize false-negatives during searches and to contextualize the users' needs. The creation of a drug information portal makes more targeted research possible, with numerous entries according to user (physicians, pharmacists, chemists, and pharmacologists). For simplicity's sake, the catalogue's index of resources by different nomenclatures is not entirely displayed. The choice of display is left to the user, with MeSH only as the default. These multi-nomenclature tools should be applicable as well to electronic patient records. In this case, the objective is to improve patient care by better searches and identification of the information required during consultations and hospitalization.

Modeling in biomedical informatics—An exploratory analysis

OBJECTIVE

Modeling is a significant part of research, education and practice in biomedical and health informatics. Our objective was to explore which types of models of processes are used in current biomedical/health informatics research, as reflected in publications of scientific journals in this field. Also, the implications for medical informatics curricula were investigated.

METHODS

Retrospective, prolective observational study on recent publications of the two official journals of the International Medical Informatics Association (IMIA), the International Journal of Medical Informatics (IJMI) and Methods of Information in Medicine (MIM). All publications of the years 2004 and 2005 from these journals were indexed according to a given list of model types. Random samples out of these publications were analysed in more depth.

RESULTS

Three hundred and eighty-four publications have been analysed, 190 of IJMI and 194 of MIM. For publications in special issues (121 in IJMI) and special topics (132 in MIM) we found differences between theme-centered and conference-centered special issues/special topics (SIT) publications. In particular, we could observe a high variation between modeling in publications of theme-centered SITs. It became obvious that often sound formal knowledge as well as a strong engineering background is needed for carrying out this type of research. Usually, this knowledge and the related skills can be best provided in consecutive B.Sc. and M.Sc. programs in medical informatics (respectively, health informatics, biomedical informatics). If the focus should be primarily on health information systems and evaluation this can be offered in a M.Sc. program in medical informatics.

CONCLUSIONS

In analysing the 384 publications it became obvious that modeling continues to be a major task in research, education and practice in biomedical and health informatics. Knowledge and skills on a broad range of model types are needed in biomedical/health informatics.

A MEDLINE categorization algorithm

Background

Categorization is designed to enhance resource description by organizing content description so as to enable the reader to grasp quickly and easily what are the main topics discussed in it. The objective of this work is to propose a categorization algorithm to classify a set of scientific articles indexed with the MeSH thesaurus, and in particular those of the MEDLINE bibliographic database. In a large bibliographic database such as MEDLINE, finding materials of particular interest to a specialty group, or relevant to a particular audience, can be difficult. The categorization refines the retrieval of indexed material. In the CISMeF terminology, metaterms can be considered as super-concepts. They were primarily conceived to improve recall in the CISMeF quality-controlled health gateway.

Methods

The MEDLINE categorization algorithm (MCA) is based on semantic links existing between MeSH terms and metaterms on the one hand and between MeSH subheadings and metaterms on the other hand. These links are used to automatically infer a list of metaterms from any MeSH term/subheading indexing. Medical librarians manually select the semantic links.

Results

The MEDLINE categorization algorithm lists the medical specialties relevant to a MEDLINE file by decreasing order of their importance. The MEDLINE categorization algorithm is available on a Web site. It can run on any MEDLINE file in a batch mode. As an example, the top 3 medical specialties for the set of 60 articles published in BioMed Central Medical Informatics & Decision Making, which are currently indexed in MEDLINE are: information science, organization and administration and medical informatics.

Conclusion

We have presented a MEDLINE categorization algorithm in order to classify the medical specialties addressed in any MEDLINE file in the form of a ranked list of relevant specialties. The categorization method introduced in this paper is based on the manual indexing of resources with MeSH (terms/subheadings) pairs by NLM indexers. This algorithm may be used as a new bibliometric tool.

Combining different standards and different approaches for health information retrieval in a quality-controlled gateway

Internet as source of information is increasing in preeminence in numerous fields, including health. We describe in this paper the CISMeF project (acronym of Catalogue and Index of French-speaking Medical Sites) which has been designed to help the health information consumers and health professionals to find what they are looking for among the numerous health documents available online. The catalogue is founded on two standards: a set of metadata and a terminology based on the MeSH thesaurus which has the same structure and use as an ontology of the medical domain. The structure of the catalogue allows us to place the project at an overlap between the present Web, which is informal, and the forthcoming Semantic Web. Many features of information retrieval and navigation through the catalogue were developed. These features take into account the kind of the end-user (health professional, medical student, patient). The CISMeF-patients catalogue is a sub-catalogue of CISMeF and is dedicated to the patients and the general public. It shares the same model as CISMeF whereas MEDLINE and MedlinePlus do not. We also propose to couple two approaches (morphological processing and data mining) to help the users by correcting and refining their queries.

Enhancing the MeSH thesaurus to retrieve French online health resources in a quality-controlled gateway

The amount of health information available on the Internet is considerable. In this context, several health gateways have been developed. Among them, CISMeF (Catalogue and Index of Health Resources in French) was designed to catalogue and index health resources in French. The goal of this article is to describe the various enhancements to the MeSH thesaurus developed by the CISMeF team to adapt this terminology to the broader field of health Internet resources instead of scientific articles for the medline bibliographic database. CISMeF uses two standard tools for organizing information: the MeSH thesaurus and several metadata element sets, in particular the Dublin Core metadata format. The heterogeneity of Internet health resources led the CISMeF team to enhance the MeSH thesaurus with the introduction of two new concepts, respectively, resource types and metaterms. CISMeF resource types are a generalization of the publication types of medline. A resource type describes the nature of the resource and MeSH keyword/qualifier pairs describe the subject of the resource. A metaterm is generally a medical specialty or a biological science, which has semantic links with one or more MeSH keywords, qualifiers and resource types. The CISMeF terminology is exploited for several tasks: resource indexing performed manually, resource categorization performed automatically, visualization and navigation through the concept hierarchies and information retrieval using the Doc'CISMeF search engine. The CISMeF health gateway uses several MeSH thesaurus enhancements to optimize information retrieval, hierarchy navigation and automatic indexing.