Using a Relational Database to Index Infectious Disease Information

Jay A. Brown
<span title="2010-05-04">2010</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vyslcn4ljzdq3jes5w7fln3qyu" style="color: black;">International Journal of Environmental Research and Public Health</a> </i> &nbsp;
Mapping medical knowledge into a relational database became possible with the availability of personal computers and user-friendly database software in the early 1990s. To create a database of medical knowledge, the domain expert works like a mapmaker to first outline the domain and then add the details, starting with the most prominent features. The resulting "intelligent database" can support the decisions of healthcare professionals. The intelligent database described in this article
more &raquo; ... profiles of 275 infectious diseases. Users can query the database for all diseases matching one or more specific criteria (symptom, endemic region of the world, or epidemiological factor). Epidemiological factors include sources (patients, water, soil, or animals), routes of entry, and insect vectors. Medical and public health professionals could use such a database as a decision-support software tool.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/ijerph7052177">doi:10.3390/ijerph7052177</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/20623018">pmid:20623018</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC2898043/">pmcid:PMC2898043</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rzqjc4ru4nhovlhv5puynwsbk4">fatcat:rzqjc4ru4nhovlhv5puynwsbk4</a> </span>
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