Ontology-Based Information Retrieval for Healthcare Systems

With the advancements of semantic web, ontology has become the crucial mechanism for representing concepts in various domains. For research and dispersal of customized healthcare services, a major challenge is to efficiently retrieve and analyze individual patient data from a large volume of heterogeneous data over a long time span. This requirement demands effective ontology-based information retrieval approaches for clinical information systems so that the pertinent information can be mined from large amount of distributed data.<br style=”background-color: transparent; box-sizing: border-box; color: #455464; font-family: ” sourcesanspro”,”helvetica neue”,”helvetica”,arial,sans-serif; font-size: 12px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px;” /><br style=”background-color: transparent; box-sizing: border-box; color: #455464; font-family: ” sourcesanspro”,”helvetica neue”,”helvetica”,arial,sans-serif; font-size: 12px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px;” />This unique and groundbreaking book highlights the key advances in ontology-based information retrieval techniques being applied in the healthcare domain and covers the following areas:<br style=”background-color: transparent; box-sizing: border-box; color: #455464; font-family: ” sourcesanspro”,”helvetica neue”,”helvetica”,arial,sans-serif; font-size: 12px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px;” /><br style=”background-color: transparent; box-sizing: border-box; color: #455464; font-family: ” sourcesanspro”,”helvetica neue”,”helvetica”,arial,sans-serif; font-size: 12px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px;” /> Semantic data integration in e-health care systems<br style=”background-color: transparent; box-sizing: border-box; color: #455464; font-family: ” sourcesanspro”,”helvetica neue”,”helvetica”,arial,sans-serif; font-size: 12px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px;” /> Keyword-based medical information retrieval<br style=”background-color: transparent; box-sizing: border-box; color: #455464; font-family: ” sourcesanspro”,”helvetica neue”,”helvetica”,arial,sans-serif; font-size: 12px; font-style: normal; font-variant: normal; font-weight: 400; letter-spacing: normal; orphans: 2; text-align: left; text-decoration: none; text-indent: 0px; text-transform: none; -webkit-text-stroke-width: 0px; white-space: normal; word-spacing: 0px;” /> Ontology-based query retrieval support for e-health implementation<br style=”background-color: transparent; box-sizing: border-box; color: #455464; font-family: ” sourcesanspro”,”helvetica neue”,”helvetica”,arial,sans-serif; font-size: 1