{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T16:03:45Z","timestamp":1772985825570,"version":"3.50.1"},"reference-count":40,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T00:00:00Z","timestamp":1771891200000},"content-version":"vor","delay-in-days":54,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"funder":[{"DOI":"10.13039\/501100001803","name":"Charles Darwin University","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001803","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Intelligent Systems"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:p>Parkinson\u2019s disease (PD) is one of the fastest\u2010growing neurodegenerative disorders, where timely diagnosis is essential for optimizing treatment. In this study, we created a radiomics\u2013MDS\u2010UPDRS, a robust dataset by integrating DaTscan SPECT radiomics data with the clinical characteristics of MDS\u2010UPDRS collected from Parkinson\u2019s progression markers initiative (PPMI) to monitor dopamine depletion in the striatum (caudate and putamen) and allow classification and progression analysis of PD. To construct the dataset, the striatum was segmented using a modified K\u2010means clustering algorithm, extracting 25 radiomics features combined with 59 clinical features. In addition, linear discriminant analysis was used to select 22 significant characteristics, and a four\u2010way feature selection method was used to identify 30 significant clinical features, resulting in a refined set of 52. Classification with machine learning models improved performance after LDA, achieving over 91% accuracy. We evaluated feature behavior across six PD severity stages and four clinical visits for progression analysis. The clinical features of MDS\u2010UPDRS were more sensitive to changes in the severity of the initial PD. At the same time, the integrated dataset, radiomics\u2013MDS\u2010UPDRS, provided more balanced insights, showing a progression of 33.30%\u201383.30% and 36.36%\u201345.50% from the first visit to the fourth visit among the clinical and radiomics features and a progression of 73.33%\u201396.67% and 13.64%\u201354.55% between the minimal vs mild and minimal vs very severe stage. Our analysis also revealed practical links between progression features and real\u2010life scenarios, which highlights the practical value of our study for clinical decision\u2010making.<\/jats:p>","DOI":"10.1155\/int\/5547118","type":"journal-article","created":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T10:19:19Z","timestamp":1772965159000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Quantitative Measurement of Parkinson Disease Progression Using DaTscan Radiomics and Clinical Features With a Machine Learning\u2013Based Approach"],"prefix":"10.1155","volume":"2026","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-2732-8710","authenticated-orcid":false,"given":"Md. Mahbub","family":"Alam","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0007-6914-2874","authenticated-orcid":false,"given":"Subhey Sadi","family":"Rahman","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0009-9034-9460","authenticated-orcid":false,"given":"Sadia Sultana","family":"Chowa","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0004-3097-8576","authenticated-orcid":false,"given":"Md. Abdur","family":"Rahman","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7209-3881","authenticated-orcid":false,"given":"Md. Rafiqul","family":"Islam","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7572-9750","authenticated-orcid":false,"given":"Sami","family":"Azam","sequence":"additional","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2026,2,24]]},"reference":[{"key":"e_1_2_13_1_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2018.02.009"},{"key":"e_1_2_13_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.zemedi.2018.11.002"},{"key":"e_1_2_13_3_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12880-024-01335-Z"},{"key":"e_1_2_13_4_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10916-015-0353-9"},{"key":"e_1_2_13_5_2","doi-asserted-by":"publisher","DOI":"10.1186\/s13550-015-0087-1"},{"key":"e_1_2_13_6_2","doi-asserted-by":"publisher","DOI":"10.1038\/srep41069"},{"key":"e_1_2_13_7_2","doi-asserted-by":"publisher","DOI":"10.1049\/iet-Ipr.2020.1048"},{"key":"e_1_2_13_8_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12967-023-04158-8"},{"key":"e_1_2_13_9_2","doi-asserted-by":"publisher","DOI":"10.1172\/jci157074"},{"key":"e_1_2_13_10_2","doi-asserted-by":"publisher","DOI":"10.1002\/mds.29678"},{"key":"e_1_2_13_11_2","doi-asserted-by":"publisher","DOI":"10.3389\/fneur.2022.1010147"},{"key":"e_1_2_13_12_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2018.05.004"},{"key":"e_1_2_13_13_2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3308075"},{"key":"e_1_2_13_14_2","doi-asserted-by":"publisher","DOI":"10.3390\/molecules25204792"},{"key":"e_1_2_13_15_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2020.104041"},{"key":"e_1_2_13_16_2","doi-asserted-by":"publisher","DOI":"10.3390\/math10152566"},{"key":"e_1_2_13_17_2","doi-asserted-by":"crossref","unstructured":"ReyesJ. F. MontealegreJ. S. CastanoY. J. UrcuquiC. andNavarroA. LSTM and Convolution Networks Exploration for Parkinson\u2019s Diagnosis Proceedings of the 2019 Ieee Colombian Conference on Communications and Computing (COLCOM) 2019 1\u20134.","DOI":"10.1109\/ColComCon.2019.8809160"},{"key":"e_1_2_13_18_2","doi-asserted-by":"crossref","unstructured":"YagisE. De HerreraA. G. S. andCitiL. Generalization Performance of Deep Learning Models in Neurodegenerative Disease Classification Proceedings of the 2019 Ieee International Conference on Bioinformatics and Biomedicine (BIBM) 2019 1692\u20131698.","DOI":"10.1109\/BIBM47256.2019.8983088"},{"key":"e_1_2_13_19_2","doi-asserted-by":"crossref","unstructured":"AliL. KhanS. U. ArshadM. AliS. andAnwarM. A Multi-Model Framework for Evaluating Type of Speech Samples Having Complementary Information About Parkinson\u2019s Disease Proceedings of the 2019 International Conference on Electrical Communication and Computer Engineering (ICECCE) 2019 1\u20135.","DOI":"10.1109\/ICECCE47252.2019.8940696"},{"key":"e_1_2_13_20_2","doi-asserted-by":"publisher","DOI":"10.3390\/s18124224"},{"key":"e_1_2_13_21_2","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2018.2794470"},{"key":"e_1_2_13_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2016.03.001"},{"key":"e_1_2_13_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejmp.2023.102647"},{"key":"e_1_2_13_24_2","doi-asserted-by":"publisher","DOI":"10.1038\/s41531-022-00409-5"},{"key":"e_1_2_13_25_2","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2021.3052652"},{"key":"e_1_2_13_26_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2018.09.008"},{"key":"e_1_2_13_27_2","doi-asserted-by":"publisher","DOI":"10.1109\/access.2019.2932037"},{"key":"e_1_2_13_28_2","doi-asserted-by":"publisher","DOI":"10.3389\/fninf.2018.00053"},{"key":"e_1_2_13_29_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00415-019-09458-Y"},{"key":"e_1_2_13_30_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-019-0987-5"},{"key":"e_1_2_13_31_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.parkreldis.2019.02.028"},{"key":"e_1_2_13_32_2","doi-asserted-by":"publisher","DOI":"10.1109\/TNSRE.2023.3330643"},{"key":"e_1_2_13_33_2","first-page":"1147","article-title":"Multi-View Graph Convolutional Network and Its Applications on Neuroimage Analysis for Parkinson\u2019s Disease","volume":"2018","author":"Zhang X.","year":"2018","journal-title":"Proceedings of the Amia Annual Symposium"},{"key":"e_1_2_13_34_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.pneurobio.2011.09.005"},{"key":"e_1_2_13_35_2","doi-asserted-by":"publisher","DOI":"10.2967\/jnumed.118.222893"},{"key":"e_1_2_13_36_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00259-020-04817-8"},{"key":"e_1_2_13_37_2","doi-asserted-by":"publisher","DOI":"10.1148\/rg.230133"},{"key":"e_1_2_13_38_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.brainres.2025.149717"},{"key":"e_1_2_13_39_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2016.02.012"},{"key":"e_1_2_13_40_2","doi-asserted-by":"publisher","DOI":"10.1155\/2014\/672630"}],"container-title":["International Journal of Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/int\/5547118","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/full-xml\/10.1155\/int\/5547118","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1155\/int\/5547118","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,8]],"date-time":"2026-03-08T10:19:21Z","timestamp":1772965161000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1155\/int\/5547118"}},"subtitle":[],"editor":[{"given":"Richard","family":"Murray","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":40,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["10.1155\/int\/5547118"],"URL":"https:\/\/doi.org\/10.1155\/int\/5547118","archive":["Portico"],"relation":{},"ISSN":["0884-8173","1098-111X"],"issn-type":[{"value":"0884-8173","type":"print"},{"value":"1098-111X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"2025-06-25","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-01-13","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2026-02-24","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"5547118"}}