{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,3]],"date-time":"2025-10-03T09:29:13Z","timestamp":1759483753774,"version":"3.37.3"},"reference-count":17,"publisher":"Wiley","license":[{"start":{"date-parts":[[2013,1,1]],"date-time":"2013-01-01T00:00:00Z","timestamp":1356998400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"funder":[{"DOI":"10.13039\/501100004096","name":"Kyushu University","doi-asserted-by":"publisher","award":["(24700286"],"award-info":[{"award-number":["(24700286"]}],"id":[{"id":"10.13039\/501100004096","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001700","name":"Ministry of Education, Culture, Sport, Science and Technology of Japan","doi-asserted-by":"crossref","award":["(24700286"],"award-info":[{"award-number":["(24700286"]}],"id":[{"id":"10.13039\/501100001700","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computational and Mathematical Methods in Medicine"],"published-print":{"date-parts":[[2013]]},"abstract":"<jats:p>Magnetic resonance imaging (MRI) data is an invaluable tool in brain morphology research. Here, we propose a novel statistical method for investigating the relationship between clinical characteristics and brain morphology based on three-dimensional MRI data via radial basis function-sparse partial least squares (RBF-sPLS). Our data consisted of MRI image intensities for multimillion voxels in a 3D array along with 73 clinical variables. This dataset represents a suitable application of RBF-sPLS because of a potential correlation among voxels as well as among clinical characteristics. Additionally, this method can simultaneously select both effective brain regions and clinical characteristics based on sparse modeling. This is in contrast to existing methods, which consider prespecified brain regions because of the computational difficulties involved in processing high-dimensional data. RBF-sPLS employs dimensionality reduction in order to overcome this obstacle. We have applied RBF-sPLS to a real dataset composed of 102 chronic kidney disease patients, while a comparison study used a simulated dataset. RBF-sPLS identified two brain regions of interest from our patient data: the temporal lobe and the occipital lobe, which are associated with aging and anemia, respectively. Our simulation study suggested that such brain regions are extracted with excellent accuracy using our method.<\/jats:p>","DOI":"10.1155\/2013\/591032","type":"journal-article","created":{"date-parts":[[2013,5,13]],"date-time":"2013-05-13T21:04:00Z","timestamp":1368479040000},"page":"1-7","source":"Crossref","is-referenced-by-count":12,"title":["Radial Basis Function-Sparse Partial Least Squares for Application to Brain Imaging Data"],"prefix":"10.1155","volume":"2013","author":[{"given":"Hisako","family":"Yoshida","sequence":"first","affiliation":[{"name":"Department of Biostatistics, Graduate School of Medicine, Kurume University, Kurume 8300011, Japan"},{"name":"Department of Integrated Therapy for Chronic Kidney Disease, Graduate School of Medical Sciences, Kyushu University, Fukuoka 8118582, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Atsushi","family":"Kawaguchi","sequence":"additional","affiliation":[{"name":"Biostatistics Center, Kurume University, Kurume 8300011, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8390-2928","authenticated-orcid":true,"given":"Kazuhiko","family":"Tsuruya","sequence":"additional","affiliation":[{"name":"Department of Integrated Therapy for Chronic Kidney Disease, Graduate School of Medical Sciences, Kyushu University, Fukuoka 8118582, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1038\/oby.2007.4"},{"issue":"3","key":"2","doi-asserted-by":"crossref","first-page":"677","DOI":"10.2337\/dc12-0814","volume":"36","year":"2013","journal-title":"Diabetes Care"},{"key":"3","first-page":"11","volume":"15","year":"2012","journal-title":"Neuroimage"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1006\/nimg.2000.0582"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2004.05.010"},{"journal-title":"Journal of Multivariate Analysis","first-page":"391","year":"1966","key":"6"},{"key":"7a","doi-asserted-by":"publisher","DOI":"10.1006\/nimg.1996.0016"},{"issue":"2","key":"7b","first-page":"169","volume":"8","year":"1994","journal-title":"Journal of Chemotherapy"},{"key":"8","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","volume":"58","year":"1996","journal-title":"Journal of the Royal Statistical Society Series B"},{"key":"9","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1214\/009053604000000067","volume":"32","year":"2004","journal-title":"Annals of Statistics"},{"issue":"1, article 35","key":"10","volume":"7","year":"2008","journal-title":"Statistical Applications in Genetics and Molecular Biology"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-9868.2009.00723.x"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1016\/S0925-2312(97)00078-7"},{"year":"1998","key":"13"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1038\/hr.2010.171"},{"issue":"7","key":"16","doi-asserted-by":"crossref","first-page":"1149","DOI":"10.4009\/jsdt.34.1149","volume":"34","year":"2001","journal-title":"Journal of the Japanese Society for Dialysis Therapy"},{"volume":"667","journal-title":"Journal of the American Society of Nephrology Supplement A","year":"2012","key":"17"}],"container-title":["Computational and Mathematical Methods in Medicine"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2013\/591032.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2013\/591032.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/cmmm\/2013\/591032.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,10]],"date-time":"2024-05-10T16:42:56Z","timestamp":1715359376000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.hindawi.com\/journals\/cmmm\/2013\/591032\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013]]},"references-count":17,"alternative-id":["591032","591032"],"URL":"https:\/\/doi.org\/10.1155\/2013\/591032","relation":{},"ISSN":["1748-670X","1748-6718"],"issn-type":[{"type":"print","value":"1748-670X"},{"type":"electronic","value":"1748-6718"}],"subject":[],"published":{"date-parts":[[2013]]}}}