{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T11:06:06Z","timestamp":1784027166158,"version":"3.55.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686677","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T00:00:00Z","timestamp":1781481600000},"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":[[2026,6,15]]},"abstract":"<jats:p>*CORRIGENDUM on final page* Drafting an Individual Rehabilitation Project requires precise goal-setting based on functional prognosis. However, patient stratification in rehabilitation is often hindered by the complexity of multimodal interventions. The PREPARE Rehab project, a four-year EU Horizon initiative, utilises Machine Learning and Artificial Intelligence (AI) to develop data-driven prediction tools across nine health conditions. This paper focuses on the children with idiopathic scoliosis cohort, utilising a dataset of over 21,000 patients. By standardising data through the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM), the project aims to deliver a unified decision-support platform and AI-enhanced stratification models to prevent adult disability and optimise treatment intensity.<\/jats:p>","DOI":"10.3233\/shti260732","type":"book-chapter","created":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T09:28:03Z","timestamp":1781515683000},"source":"Crossref","is-referenced-by-count":0,"title":["PREPARE: Personalised Rehabilitation via Novel AI Patient Stratification Strategies. The Case for Idiopathic Scoliosis During Growth"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8500-7751","authenticated-orcid":false,"given":"Carlotte","family":"Kiekens","sequence":"first","affiliation":[{"name":"Laboratory of Evidence-Based rehabilitation, IRCCS Galeazzi-Sant\u2019Ambrogio Hospital, Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"PREPARE Group","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1878-2747","authenticated-orcid":false,"given":"Stefano","family":"Negrini","sequence":"additional","affiliation":[{"name":"Laboratory of Evidence-Based rehabilitation, IRCCS Galeazzi-Sant\u2019Ambrogio Hospital, Milan, Italy"},{"name":"Department of Biomedical, Surgical and Dental Sciences, University of Milan \u201cLa Statale\u201d, Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Research into Spinal Deformities 12"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI260732","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T10:38:12Z","timestamp":1784025492000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI260732"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6,15]]},"ISBN":["9781643686677"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti260732","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6,15]]}}}