Search PubMedSearch

PubMed · 8947749

The "SentiWeb" method for exploring a database on the Net.

Abstract

Return of information is one of the main goals of any public health information system. About 25,000 maps and 10,000 graphs may be obtained from the time-series collected in the database of the French Communicable Diseases Network (FCDN). Furthermore, this huge epidemiological atlas is updated each week. What is the optimal way of returning such information? This report discloses the strategies used for enhancing the access facilities to the FCDN database for any users, particularly those without specific training in epidemiology or database query language. The technical options implemented in the SentiWeb server (http:/(/)www.b3e.jussieu.fr) are discussed.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

E Boussard, A Flahault. 1996. The "SentiWeb" method for exploring a database on the Net.. https://pubmed.ncbi.nlm.nih.gov/8947749/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Derivation of the linear-logistic model and Cox's proportional hazard model from a canonical system description.

The linear-logistic regression model and Cox's proportional hazard model are widely used in epidemiology. Their successful application leaves no doubt that they are accurate reflections of observed disease processes and their associated risks or incidence rates. In spite of their prominence, it is not a priori evident why these models work. This article presents a derivation of the two models from the framework of canonical modeling. It begins with a general description of the dynamics between risk sources and disease development, formulates this description in the canonical representation of an S-system, and shows how the linear-logistic model and Cox's proportional hazard model follow naturally from this representation. The article interprets the model parameters in terms of epidemiological concepts as well as in terms of general systems theory and explains the assumptions and limitations generally accepted in the application of these epidemiological models.

Communicable Diseases