{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,28]],"date-time":"2025-04-28T15:31:54Z","timestamp":1745854314741},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T00:00:00Z","timestamp":1653436800000},"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":[[2022,5,25]]},"abstract":"<jats:p>Type 2 diabetes mellitus is a metabolic disorder of glucose management, whose prevalence is increasing inexorably worldwide. Adherence to therapies, along with a healthy lifestyle can help prevent the onset of disease. This preliminary study proposes the use of explainable artificial intelligence techniques with the aim of (i) characterizing diabetic patients through a set of easily interpretable rules and (ii) providing individualized recommendations for the prevention of the onset of the disease through the generation of counterfactual explanations, based on minimal variations of biomarkers routinely collected in primary care. The results of this preliminary study parallel findings from the literature as differences in biomarkers between patients with and without diabetes are observed for fasting blood sugar, body mass index, and high-density lipoprotein levels.<\/jats:p>","DOI":"10.3233\/shti220404","type":"book-chapter","created":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T12:12:46Z","timestamp":1653480766000},"source":"Crossref","is-referenced-by-count":4,"title":["Characterization of Type 2 Diabetes Using Counterfactuals and Explainable AI"],"prefix":"10.3233","author":[{"given":"Marta","family":"Lenatti","sequence":"first","affiliation":[{"name":"National Research Council of Italy (CNR), Institute of Electronics, Information Engineering and Telecommunications (IEIIT), Italy"}]},{"given":"Alberto","family":"Carlevaro","sequence":"additional","affiliation":[{"name":"National Research Council of Italy (CNR), Institute of Electronics, Information Engineering and Telecommunications (IEIIT), Italy"},{"name":"University of Genoa, Department of Electrical, Electronics and Telecommunications Engineering and Naval Architecture (DITEN), Italy"}]},{"given":"Karim","family":"Keshavjee","sequence":"additional","affiliation":[{"name":"University of Toronto, Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, Canada"}]},{"given":"Aziz","family":"Guergachi","sequence":"additional","affiliation":[{"name":"Ryerson University, Ted Rogers School of Management, Toronto, Canada"},{"name":"York University, Department of Mathematics and Statistics, Toronto, Canada"}]},{"given":"Alessia","family":"Paglialonga","sequence":"additional","affiliation":[{"name":"National Research Council of Italy (CNR), Institute of Electronics, Information Engineering and Telecommunications (IEIIT), Italy"}]},{"given":"Maurizio","family":"Mongelli","sequence":"additional","affiliation":[{"name":"National Research Council of Italy (CNR), Institute of Electronics, Information Engineering and Telecommunications (IEIIT), Italy"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Challenges of Trustable AI and Added-Value on Health"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI220404","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,25]],"date-time":"2022-05-25T12:12:47Z","timestamp":1653480767000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI220404"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,5,25]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti220404","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,5,25]]}}}