{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T13:34:04Z","timestamp":1769693644551,"version":"3.49.0"},"reference-count":56,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100007225","name":"Ministry of Science and Technology","doi-asserted-by":"publisher","award":["MOST 109-2221-E-194-053-MY3"],"award-info":[{"award-number":["MOST 109-2221-E-194-053-MY3"]}],"id":[{"id":"10.13039\/100007225","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Health Informatics J"],"published-print":{"date-parts":[[2022,10]]},"abstract":"<jats:p> A history of brain tumor strongly affects children\u2019s cognitive abilities, performance of daily activities, quality of life, and functional outcomes. In light of the difficulties in cognition, communication, physical skills, and behavior that these patients may encounter, occupational therapists should perform a comprehensive needs-led assessment of their global functioning after recovery. Such an assessment would ensure that the patients receive adequate support and services at school, at home, and in the community. By predicting the functional activity performance of children with a history of brain tumor, clinical workers can determine the progress of their ability recovery and the optimal treatment plan. We selected several features for testing and employed common machine learning models to predict Functional Independence Measure (WeeFIM) scores. The ensemble learning models exhibited stronger predictive performance than did the individual machine learning models. The ensemble learning models effectively predicted WeeFIM scores. Machine learning models can help clinical workers predict the functional assessment scores of patients with childhood brain tumors. This study used machine learning models to predict the WeeFIM scores of patients with childhood brain tumors and to demonstrate that ensemble machine learning models are more suitable for this task than are individual machine learning models. <\/jats:p>","DOI":"10.1177\/14604582221140975","type":"journal-article","created":{"date-parts":[[2022,11,22]],"date-time":"2022-11-22T17:04:13Z","timestamp":1669136653000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":4,"title":["Ensemble learning based functional independence ability estimator for pediatric brain tumor survivors"],"prefix":"10.1177","volume":"28","author":[{"given":"Pei-Hua","family":"Lin","sequence":"first","affiliation":[{"name":"Department of Rehabilitation, An Nan Hospital, China Medical University, Tainan, Taiwan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5125-4420","authenticated-orcid":false,"given":"Ping-Huan","family":"Kuo","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, National Chung Cheng University, Taiwan; Advanced Institute of Manufacturing with High-Tech Innovations, National Chung Cheng University, Taiwan"}]}],"member":"179","published-online":{"date-parts":[[2022,11,22]]},"reference":[{"key":"bibr1-14604582221140975","doi-asserted-by":"publisher","DOI":"10.15586\/codon.glioblastoma.2017.ch15"},{"key":"bibr2-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1007\/s11060-013-1212-5"},{"key":"bibr3-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1158\/1055-9965.EPI-14-0207"},{"key":"bibr4-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1177\/0883073815600866"},{"key":"bibr5-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/j.clon.2012.09.008"},{"key":"bibr6-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2004.07.073"},{"key":"bibr7-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/j.ncl.2018.04.009"},{"key":"bibr8-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/j.critrevonc.2007.03.004"},{"key":"bibr9-14604582221140975","doi-asserted-by":"publisher","DOI":"10.5014\/ajot.2016.014993"},{"key":"bibr10-14604582221140975","doi-asserted-by":"publisher","DOI":"10.3109\/02699052.2010.536194"},{"key":"bibr11-14604582221140975","doi-asserted-by":"publisher","DOI":"10.4276\/030802214X14071472109950"},{"key":"bibr12-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1177\/0308022620941396"},{"key":"bibr13-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1080\/02796015.2006.12088005"},{"key":"bibr14-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1542\/peds.109.2.e36"},{"key":"bibr15-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1177\/14604582211024698"},{"key":"bibr16-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1177\/1460458220957486"},{"key":"bibr17-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1177\/1460458219881007"},{"key":"bibr18-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104320"},{"key":"bibr19-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104564"},{"key":"bibr20-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.103804"},{"key":"bibr21-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2019.103345"},{"key":"bibr22-14604582221140975","first-page":"3967","volume":"67","author":"Noreen N","year":"2021","journal-title":"Comput Mater Contin"},{"key":"bibr23-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-48738-5"},{"key":"bibr24-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-021-82214-3"},{"key":"bibr25-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2020.102172"},{"key":"bibr26-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.103758"},{"key":"bibr27-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2020.102506"},{"key":"bibr28-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1093\/neuonc\/noz184"},{"key":"bibr29-14604582221140975","doi-asserted-by":"publisher","DOI":"10.18632\/aging.103923"},{"key":"bibr30-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1177\/1460458220983878"},{"key":"bibr31-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1177\/1460458218824692"},{"key":"bibr32-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1177\/1460458219855884"},{"key":"bibr33-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1177\/1460458221989402"},{"key":"bibr34-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1177\/14604582211007537"},{"key":"bibr35-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1177\/14604582211021471"},{"key":"bibr36-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1177\/1460458219898568"},{"key":"bibr37-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2014.11.009"},{"key":"bibr38-14604582221140975","doi-asserted-by":"publisher","DOI":"10.3233\/PRM-2011-0154"},{"key":"bibr39-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2016.07.005"},{"key":"bibr40-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.04.018"},{"key":"bibr41-14604582221140975","doi-asserted-by":"crossref","unstructured":"Zhang F, O\u2019Donnell LJ. Support vector regression. In: Machine learning. Amsterdam, Netherlands: Elsevier, 2020, pp. 123\u2013140.","DOI":"10.1016\/B978-0-12-815739-8.00007-9"},{"key":"bibr42-14604582221140975","first-page":"130","volume":"27","author":"Song Y-Y","year":"2015","journal-title":"Shanghai Arch Psychiat"},{"issue":"1","key":"bibr43-14604582221140975","first-page":"1","volume":"2","author":"Patel BR","year":"2014","journal-title":"International Journal of Engineering Development and Research"},{"key":"bibr44-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1890\/07-0539.1"},{"key":"bibr45-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-444-63623-2.00007-4"},{"key":"bibr46-14604582221140975","doi-asserted-by":"publisher","DOI":"10.3724\/SP.J.1004.2013.00745"},{"key":"bibr47-14604582221140975","doi-asserted-by":"publisher","DOI":"10.3390\/cancers13194776"},{"key":"bibr48-14604582221140975","doi-asserted-by":"publisher","DOI":"10.5281\/zenodo.4733570"},{"key":"bibr49-14604582221140975","first-page":"21","volume":"2","author":"Razali NM","year":"2011","journal-title":"J Stat Model Anal"},{"key":"bibr50-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/j.pmrj.2015.10.012"},{"key":"bibr51-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1080\/09297049.2012.669470"},{"key":"bibr52-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.5220-13.2014"},{"key":"bibr53-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1007\/s00381-016-3170-7"},{"key":"bibr54-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1002\/pbc.26203"},{"key":"bibr55-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1177\/0308022620939859"},{"key":"bibr56-14604582221140975","doi-asserted-by":"publisher","DOI":"10.1016\/j.soncn.2019.150984"}],"container-title":["Health Informatics Journal"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/14604582221140975","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/14604582221140975","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/14604582221140975","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,3,2]],"date-time":"2025-03-02T15:34:57Z","timestamp":1740929697000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/14604582221140975"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10]]},"references-count":56,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2022,10]]}},"alternative-id":["10.1177\/14604582221140975"],"URL":"https:\/\/doi.org\/10.1177\/14604582221140975","relation":{},"ISSN":["1460-4582","1741-2811"],"issn-type":[{"value":"1460-4582","type":"print"},{"value":"1741-2811","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10]]},"article-number":"14604582221140975"}}