{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T09:48:52Z","timestamp":1747216132562,"version":"3.40.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"print","value":"9781643683881"},{"type":"electronic","value":"9781643683898"}],"license":[{"start":{"date-parts":[[2023,5,18]],"date-time":"2023-05-18T00:00:00Z","timestamp":1684368000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,5,18]]},"abstract":"<jats:p>With the advent of SARS-CoV-2, several studies have shown that there is a higher mortality rate in patients with diabetes and, in some cases, it is one of the side effects of overcoming the disease. However, there is no clinical decision support tool or specific treatment protocols for these patients. To tackle this issue, in this paper we present a Pharmacological Decision Support System (PDSS) providing intelligent decision support for COVID-19 diabetic patient treatment selection, based on an analysis of risk factors with data from electronic medical records using Cox regression. The goal of the system is to create real world evidence including the ability to continuously learn to improve clinical practice and outcomes of diabetic patients with COVID-19.<\/jats:p>","DOI":"10.3233\/shti230197","type":"book-chapter","created":{"date-parts":[[2023,5,19]],"date-time":"2023-05-19T04:45:24Z","timestamp":1684471524000},"source":"Crossref","is-referenced-by-count":0,"title":["PDSS: A Pharmacological Decision Support System for Diabetics Patients with COVID-19"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1073-7116","authenticated-orcid":false,"given":"Isabel","family":"Amaya-Rodriguez","sequence":"first","affiliation":[{"name":"Department of Computer Science, University of Seville, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0248-7783","authenticated-orcid":false,"given":"Nekane","family":"Larburu","sequence":"additional","affiliation":[{"name":"Biodonostia Health Research Institute, (Bioengineering Area), eHealth Group, San Sebasti\u00e1n 20014, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4667-521X","authenticated-orcid":false,"given":"Mar\u00eda Roll\u00e1n","family":"Martinez-Herrera","sequence":"additional","affiliation":[{"name":"Applied Chest Imaging Laboratory, Brigham and Women\u2019s Hospital, Harvard Medical School, Boston, MA, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8169-9655","authenticated-orcid":false,"given":"Kristin","family":"Rebescher","sequence":"additional","affiliation":[{"name":"Biodonostia Health Research Institute, (Bioengineering Area), eHealth Group, San Sebasti\u00e1n 20014, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0448-7840","authenticated-orcid":false,"given":"Iv\u00e1n","family":"Macia","sequence":"additional","affiliation":[{"name":"Biodonostia Health Research Institute, (Bioengineering Area), eHealth Group, San Sebasti\u00e1n 20014, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7012-2973","authenticated-orcid":false,"given":"Miguel A.","family":"Armengol De La Hoz","sequence":"additional","affiliation":[{"name":"Big Data Department \u2013 Regional Ministry of Health of Southern Spain, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5732-9139","authenticated-orcid":false,"given":"Cristina","family":"Rubio-Escudero","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Seville, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7160-1191","authenticated-orcid":false,"given":"Alba","family":"Garin-Muga","sequence":"additional","affiliation":[{"name":"Biodonostia Health Research Institute, (Bioengineering Area), eHealth Group, San Sebasti\u00e1n 20014, Spain"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Caring is Sharing \u2013 Exploiting the Value in Data for Health and Innovation"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI230197","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,31]],"date-time":"2023-05-31T10:59:05Z","timestamp":1685530745000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI230197"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,18]]},"ISBN":["9781643683881","9781643683898"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti230197","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2023,5,18]]}}}