LEADER 00974cam2 22002651 450 001 SOBE00038178 005 20131204095418.0 100 $a20131204d1927 |||||ita|0103 ba 101 $aita 102 $aIT 200 0 $a2 210 $aFirenze$cLibreria Editrice Fiorentina$d1927 215 $a315-717 p.$d20 cm 225 2 $alibri della fede$v24 410 1$1001SOBE00038175$12001 $aI *libri della fede$v24 461 1$1001SOBE00038173$12001 $a<>antico dramma sacro italiano / scelta e prefazione di Paolo Toschi 801 0$aIT$bUNISOB$c20131204$gRICA 850 $aUNISOB 852 $aUNISOB$j3|A$m12265|ort 912 $aSOBE00038178 940 $aM 102 Monografia moderna SBN 941 $aW 957 $xFondo|Ortolani$a3|A$b017$i-6.2$fModalità di consultazione sulla home page della Biblioteca link Fondi$gNO$d12265|ort$hOrtolaniS$rdono$1calvano123$2UNISOB$3UNISOB$420131204095439.0$520131204095539.0$6calvano123 996 $a2$961340 997 $aUNISOB LEADER 02145oam 2200421zu 450 001 996202055003316 005 20210807002657.0 010 $a1-5090-8690-0 035 $a(CKB)1000000000331073 035 $a(SSID)ssj0000451855 035 $a(PQKBManifestationID)12140694 035 $a(PQKBTitleCode)TC0000451855 035 $a(PQKBWorkID)10463377 035 $a(PQKB)11718263 035 $a(NjHacI)991000000000331073 035 $a(EXLCZ)991000000000331073 100 $a20160829d2007 uy 101 0 $aeng 135 $aur||||||||||| 181 $ctxt 182 $cc 183 $acr 200 00$a20th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2007): Maribor, Slovenia 20-22 June 2007 210 31$a[Place of publication not identified]$cIEEE Computer Society Press$d2007 215 $a1 online resource (750, 118 papers pages) $cillustrations 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a0-7695-2905-4 330 $aIn this paper, we present a modelling framework for patient flow in a healthcare system using semi-open queueing network models, which introduces a total bed constraint, above which new patients will be refused admission. Hence this model provides a realistic representation of a real system. This approach enables us to have access to a range of established methods that deals with queueing network models. We demonstrate the usefulness of the model in the context of a geriatric department and show that hospital managers can use this model to gain better understanding of the dynamics of patient flow and to study potential long-term impacts of policy changes. 606 $aArtificial intelligence$xMedical applications$vCongresses 606 $aMedicine$xData processing$vCongresses 615 0$aArtificial intelligence$xMedical applications 615 0$aMedicine$xData processing 676 $a610.28563 801 0$bPQKB 906 $aPROCEEDING 912 $a996202055003316 996 $a20th IEEE International Symposium on Computer-Based Medical Systems (CBMS 2007): Maribor, Slovenia 20-22 June 2007$92415643 997 $aUNISA