{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,23]],"date-time":"2026-02-23T13:58:33Z","timestamp":1771855113660,"version":"3.50.1"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685335","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,8,22]],"date-time":"2024-08-22T00:00:00Z","timestamp":1724284800000},"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":[[2024,8,22]]},"abstract":"<jats:p>Causal Deep\/Machine Learning (CDL\/CML) is an emerging Artificial Intelligence (AI) paradigm. The combination of causal inference and AI could mine explainable causal relationships between data features, providing useful insights for various applications, e.g. Pharmacovigilance (PV) signal detection upon Real-World Data. The objective of this study is to demonstrate the use of CDL for potential PV signal validation using Electronic Health Records as input data source.<\/jats:p>","DOI":"10.3233\/shti240533","type":"book-chapter","created":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T09:43:10Z","timestamp":1724406190000},"source":"Crossref","is-referenced-by-count":6,"title":["Causal Deep Learning for the Detection of Adverse Drug Reactions: Drug-Induced Acute Kidney Injury as a Case Study"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6356-9531","authenticated-orcid":false,"given":"Stella","family":"Dimitsaki","sequence":"first","affiliation":[{"name":"Sorbonne Universit\u00e9, INSERM, Univ Paris 13, Laboratoire d\u2019Informatique M\u00e9dicale et d\u2019Ing\u00e9nierie des Connaissances pour la eSant\u00e9, LIMICS, F-75006 Paris, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4061-9815","authenticated-orcid":false,"given":"Pantelis","family":"Natsiavas","sequence":"additional","affiliation":[{"name":"Institute of Applied Biosciences, Centre for Research and Development Hellas, Thessaloniki, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4445-7494","authenticated-orcid":false,"given":"Marie-Christine","family":"Jaulent","sequence":"additional","affiliation":[{"name":"Sorbonne Universit\u00e9, INSERM, Univ Paris 13, Laboratoire d\u2019Informatique M\u00e9dicale et d\u2019Ing\u00e9nierie des Connaissances pour la eSant\u00e9, LIMICS, F-75006 Paris, France"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Digital Health and Informatics Innovations for Sustainable Health Care Systems"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI240533","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,23]],"date-time":"2024-08-23T09:43:11Z","timestamp":1724406191000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI240533"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,22]]},"ISBN":["9781643685335"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti240533","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,22]]}}}