{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,4,5]],"date-time":"2022-04-05T08:59:15Z","timestamp":1649149155778},"reference-count":0,"publisher":"IOS Press","license":[{"start":{"date-parts":[[2022,1,14]],"date-time":"2022-01-14T00:00:00Z","timestamp":1642118400000},"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":[[2022,1,14]]},"abstract":"<jats:p>Zoning classification is a rating mechanism, which uses a three-tier color coding to indicate perceived risk from the patients\u2019 conditions. It is a widely adopted manual system used across mental health settings, however it is time consuming and costly. We propose to automate classification, by adopting a hybrid approach, which combines Temporal Abstraction to capture the temporal relationship between symptoms and patients\u2019 behaviors, Natural Language Processing to quantify statistical information from patient notes, and Supervised Machine Learning Models to make a final prediction of zoning classification for mental health patients.<\/jats:p>","DOI":"10.3233\/shti210924","type":"book-chapter","created":{"date-parts":[[2022,1,17]],"date-time":"2022-01-17T15:55:45Z","timestamp":1642434945000},"source":"Crossref","is-referenced-by-count":0,"title":["A Conceptual Framework to Predict Mental Health Patients\u2019 Zoning Classification"],"prefix":"10.3233","author":[{"given":"Sanjib Raj","family":"Pandey","sequence":"first","affiliation":[{"name":"School of Computer Science & Engineering, University of Westminster, London, UK"}]},{"given":"Alan","family":"Smith","sequence":"additional","affiliation":[{"name":"Business Intelligence Systems Team, Oxleas NHS Foundation Trust, London, UK"}]},{"given":"Edmund Nigel","family":"Gall","sequence":"additional","affiliation":[{"name":"School of Computer Science & Engineering, University of Westminster, London, UK"}]},{"given":"Ajay","family":"Bhatnagar","sequence":"additional","affiliation":[{"name":"Green Parks House (Inpatient Services), Oxleas NHS Foundation Trust, London, UK"}]},{"given":"Thierry","family":"Chaussalet","sequence":"additional","affiliation":[{"name":"School of Computer Science & Engineering, University of Westminster, London, UK"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Informatics and Technology in Clinical Care and Public Health"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI210924","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,17]],"date-time":"2022-01-17T15:55:46Z","timestamp":1642434946000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI210924"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,14]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti210924","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,14]]}}}