{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,2]],"date-time":"2025-11-02T11:00:00Z","timestamp":1762081200750,"version":"build-2065373602"},"reference-count":50,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T00:00:00Z","timestamp":1670803200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61901063","61875022","19YJCZH120","CE20205042","CJ20220151","2020"],"award-info":[{"award-number":["61901063","61875022","19YJCZH120","CE20205042","CJ20220151","2020"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"MOE (Ministry of Education in China) Project of Humanities and Social Sciences","award":["61901063","61875022","19YJCZH120","CE20205042","CJ20220151","2020"],"award-info":[{"award-number":["61901063","61875022","19YJCZH120","CE20205042","CJ20220151","2020"]}]},{"name":"Science and Technology Plan Project of Changzhou","award":["61901063","61875022","19YJCZH120","CE20205042","CJ20220151","2020"],"award-info":[{"award-number":["61901063","61875022","19YJCZH120","CE20205042","CJ20220151","2020"]}]},{"name":"Qing Lan Project of Jiangsu Province","award":["61901063","61875022","19YJCZH120","CE20205042","CJ20220151","2020"],"award-info":[{"award-number":["61901063","61875022","19YJCZH120","CE20205042","CJ20220151","2020"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Genes"],"abstract":"<jats:p>In the studies of Alzheimer\u2019s disease (AD), jointly analyzing imaging data and genetic data provides an effective method to explore the potential biomarkers of AD. AD can be separated into healthy controls (HC), early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI) and AD. In the meantime, identifying the important biomarkers of AD progression, and analyzing these biomarkers in AD provide valuable insights into understanding the mechanism of AD. In this paper, we present a novel data fusion method and a genetic weighted random forest method to mine important features. Specifically, we amplify the difference among AD, LMCI, EMCI and HC by introducing eigenvalues calculated from the gene p-value matrix for feature fusion. Furthermore, we construct the genetic weighted random forest using the resulting fused features. Genetic evolution is used to increase the diversity among decision trees and the decision trees generated are weighted by weights. After training, the genetic weighted random forest is analyzed further to detect the significant fused features. The validation experiments highlight the performance and generalization of our proposed model. We analyze the biological significance of the results and identify some significant genes (CSMD1, CDH13, PTPRD, MACROD2 and WWOX). Furthermore, the calcium signaling pathway, arrhythmogenic right ventricular cardiomyopathy and the glutamatergic synapse pathway were identified. The investigational findings demonstrate that our proposed model presents an accurate and efficient approach to identifying significant biomarkers in AD.<\/jats:p>","DOI":"10.3390\/genes13122344","type":"journal-article","created":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T05:10:19Z","timestamp":1670821819000},"page":"2344","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Detection of Association Features Based on Gene Eigenvalues and MRI Imaging Using Genetic Weighted Random Forest"],"prefix":"10.3390","volume":"13","author":[{"given":"Zhixi","family":"Hu","sequence":"first","affiliation":[{"name":"School of Computer Information and Engineering, Changzhou Institute of Technology, Changzhou 213032, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuanyan","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Information and Engineering, Changzhou Institute of Technology, Changzhou 213032, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Physics, Engineering and Computer Science, University of Hertfordshire, Hatfield AL10 9AB, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3220-5820","authenticated-orcid":false,"given":"Wenjie","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Information and Engineering, Changzhou Institute of Technology, Changzhou 213032, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feng","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Electrical & Information Engineering, Changzhou Institute of Technology, Changzhou 213032, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xianglian","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Computer Information and Engineering, Changzhou Institute of Technology, Changzhou 213032, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Alzheimer\u2019s Association (2019). 2019 Alzheimer\u2019s disease facts and figures. 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