{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T01:03:41Z","timestamp":1755219821815,"version":"3.43.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686080","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"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":[[2025,8,7]]},"abstract":"<jats:p>The popularization of artificial intelligence solutions in both research and industry that has been occurring due to the rise of tools such as the GPT, Gemini and Claude large language models has revitalized research in the area. There are many possible uses within the medical field, but a key determinant of the adoption of new tools by medical professionals is trust. To augment tool trust, the tool must be made understandable and explainable, but this is a problem for \u201cblack box\u201d machine learning models. In an effort to promote transparency, we have performed a deep study of the reasoning behind an XGBoost machine learning model that performed well in the task of inpatient admission prediction.<\/jats:p>","DOI":"10.3233\/shti250908","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:34:48Z","timestamp":1754566488000},"source":"Crossref","is-referenced-by-count":0,"title":["Explaining Machine Learning: A Deeper Look into Admission Prediction"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0656-511X","authenticated-orcid":false,"given":"Bernardo","family":"Consoli","sequence":"first","affiliation":[{"name":"Pontifical Catholic University of Rio Grande do Sul"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vin\u00edcius","family":"Pedroso","sequence":"additional","affiliation":[{"name":"Pontifical Catholic University of Rio Grande do Sul"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Artur","family":"Kniest","sequence":"additional","affiliation":[{"name":"Pontifical Catholic University of Rio Grande do Sul"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Renata","family":"Vieira","sequence":"additional","affiliation":[{"name":"University of \u00c9vora"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rafael H.","family":"Bordini","sequence":"additional","affiliation":[{"name":"Pontifical Catholic University of Rio Grande do Sul"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Isabel H.","family":"Manssour","sequence":"additional","affiliation":[{"name":"Pontifical Catholic University of Rio Grande do Sul"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2025 \u2014 Healthcare Smart \u00d7 Medicine Deep"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI250908","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:34:48Z","timestamp":1754566488000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI250908"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti250908","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,7]]}}}