Combination of heterogeneous criteria for the automatic detection of ethical principles on health web sites.

TitleCombination of heterogeneous criteria for the automatic detection of ethical principles on health web sites.
Publication TypeJournal Article
Year of Publication2007
AuthorsGaudinat, A, Grabar, N, Boyer, C
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
Pagination264-8
Date Published2007
ISSN1942-597X
KeywordsAlgorithms, Artificial Intelligence, Codes of Ethics, Health, Humans, Information Services, Internet, Natural Language Processing, Quality Control
Abstract

The detection of ethical issues of web sites aims at selection of information helpful to the reader and is an important concern in medical informatics. Indeed, with the ever-increasing volume of online health information, coupled with its uneven reliability and quality, the public should be aware about the quality of information available online. In order to address this issue, we propose methods for the automatic detection of statements related to ethical principles such as those of the HONcode. For the detection of these statements, we combine two kinds of heterogeneous information: content-based categorizations and URL-based categorizations through application of the machine learning algorithms. Our objective is to observe the quality of categorization through URL's for web pages where categorization through content has been proven to be not precise enough. The results obtained indicate that only some of the principles were better processed.

URLhttp://bitem.hesge.ch/sites/default/files/biblio/AMIA-0862-S2007.pdf
Alternate JournalAMIA Annu Symp Proc
PubMed ID18693839