{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T18:06:40Z","timestamp":1760551600396,"version":"3.37.3"},"reference-count":48,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2021,11,19]],"date-time":"2021-11-19T00:00:00Z","timestamp":1637280000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,11,19]],"date-time":"2021-11-19T00:00:00Z","timestamp":1637280000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Sign Process Syst"],"published-print":{"date-parts":[[2022,11]]},"DOI":"10.1007\/s11265-021-01717-4","type":"journal-article","created":{"date-parts":[[2021,11,19]],"date-time":"2021-11-19T03:02:34Z","timestamp":1637290954000},"page":"1183-1198","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Novel Data Mining Analysis Method on Risk Prediction of Type 2 Diabetes"],"prefix":"10.1007","volume":"94","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4513-8498","authenticated-orcid":false,"given":"Hong","family":"Guo","sequence":"first","affiliation":[]},{"given":"ZhiChao","family":"Fan","sequence":"additional","affiliation":[]},{"given":"Yan","family":"Zeng","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,11,19]]},"reference":[{"key":"1717_CR1","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1016\/j.diabres.2018.02.023","volume":"138","author":"NH Cho","year":"2018","unstructured":"Cho, N. H., Shaw, J. E., Karuranga, S., et al. (2018). IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Research & Clinical Practice, 138, 271\u2013281.","journal-title":"Diabetes Research & Clinical Practice"},{"issue":"S1","key":"1717_CR2","first-page":"S5","volume":"26","author":"American Diabetes Association","year":"2003","unstructured":"American Diabetes Association. (2003). Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care, 26(S1), S5\u2013S20.","journal-title":"Diabetes Care"},{"key":"1717_CR3","first-page":"75","volume":"6","author":"Z Hu","year":"2019","unstructured":"Hu, Z. (2019). Complications of diabetes and its harm. Home Medicine, 6, 75.","journal-title":"Home Medicine"},{"key":"1717_CR4","unstructured":"Diabetes Branch of Chinese Medical Association. (2021). Guideline for the prevention and treatment of type 2 diabetes mellitus in China (2020 edition). Chinese Journal of Diabetes Mellitus, 13(4), 315-409."},{"issue":"4","key":"1717_CR5","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1109\/LES.2014.2344913","volume":"6","author":"M Qiu","year":"2014","unstructured":"Qiu, M., Chen, Z., & Liu, M. (2014). Low-power low-latency data allocation for hybrid scratch-pad memory. IEEE Embedded Systems Letters, 6(4), 69\u201372.","journal-title":"IEEE Embedded Systems Letters"},{"key":"1717_CR6","doi-asserted-by":"crossref","unstructured":"Gao, Y., Iqbal, S., et al. (2015). Performance and power analysis of high-density multi-GPGPU architectures: A preliminary case study.\u00a0IEEE 17th HPCC.","DOI":"10.1109\/HPCC-CSS-ICESS.2015.68"},{"issue":"10","key":"1717_CR7","doi-asserted-by":"publisher","first-page":"439","DOI":"10.1016\/j.sysarc.2012.07.001","volume":"58","author":"M Qiu","year":"2012","unstructured":"Qiu, M., Ming, Z., Li, J., Liu, S., Wang, B., & Lu, Z. (2012). Three-phase time-aware energy minimization with DVFS and unrolling for chip multiprocessors. Journal of Systems Architecture, 58(10), 439\u2013445.","journal-title":"Journal of Systems Architecture"},{"key":"1717_CR8","doi-asserted-by":"crossref","unstructured":"Tao, L., Golikov, S., et al. (2015). A reusable software component for integrated syntax and semantic validation for services computing, IEEE Symposium on Service-Oriented System Engineering, 127-132","DOI":"10.1109\/SOSE.2015.10"},{"issue":"3","key":"1717_CR9","doi-asserted-by":"publisher","first-page":"245","DOI":"10.1007\/s00530-004-0155-2","volume":"10","author":"K Zhang","year":"2005","unstructured":"Zhang, K., Kong, J., Qiu, M., & Song, G. (2005). Multimedia layout adaptation through grammatical specifications. Multimedia Systems, 10(3), 245\u2013260.","journal-title":"Multimedia Systems"},{"issue":"2","key":"1717_CR10","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1007\/s11265-009-0362-3","volume":"58","author":"L Zhang","year":"2010","unstructured":"Zhang, L., Qiu, M., Tseng, W., & Sha, E. (2010). Variable partitioning and scheduling for MPSoC with virtually shared scratch pad memory. Journal of Signal Processing Systems, 58(2), 247\u2013265.","journal-title":"Journal of Signal Processing Systems"},{"issue":"4","key":"1717_CR11","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1016\/j.jpdc.2011.12.004","volume":"72","author":"X Tang","year":"2012","unstructured":"Tang, X., Li, K., et al. (2012). A hierarchical reliability-driven scheduling algorithm in grid systems. Journal of Parallel and Distributed Computing, 72(4), 525\u2013535.","journal-title":"Journal of Parallel and Distributed Computing"},{"issue":"4\u20135","key":"1717_CR12","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1016\/j.sysarc.2012.12.003","volume":"59","author":"M Qiu","year":"2013","unstructured":"Qiu, M., Ming, Z., Li, J., Liu, J., Quan, G., & Zhu, Y. (2013). Informer homed routing fault tolerance mechanism for wireless sensor networks. Journal of Systems Architecture, 59(4\u20135), 260\u2013270.","journal-title":"Journal of Systems Architecture"},{"key":"1717_CR13","doi-asserted-by":"crossref","unstructured":"Gai, K., Qiu,\u00a0M., Chen, L., & Liu, M. (2015). Electronic health record error prevention approach using ontology in big data. IEEE 17th HPCC Conference, pp 752-757.","DOI":"10.1109\/HPCC-CSS-ICESS.2015.168"},{"issue":"9","key":"1717_CR14","doi-asserted-by":"publisher","first-page":"1630","DOI":"10.1109\/TKDE.2018.2866863","volume":"31","author":"R Lu","year":"2018","unstructured":"Lu, R., Jin, X., Zhang, S., Qiu, M., & Wu, X. (2018). A study on big knowledge and its engineering issues. IEEE Transactions on Knowledge and Data Engineering, 31(9), 1630\u20131644.","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"6","key":"1717_CR15","doi-asserted-by":"publisher","first-page":"809","DOI":"10.1109\/TCAD.2013.2238990","volume":"32","author":"Y Guo","year":"2013","unstructured":"Guo, Y., Zhuge, Q., Hu, J., et al. (2013). Data placement and duplication for embedded multicore systems with scratch pad memory. IEEE Transactions on Computer Aided Design Integral Circuits Systems, 32(6), 809\u2013817.","journal-title":"IEEE Transactions on Computer Aided Design Integral Circuits Systems"},{"issue":"3","key":"1717_CR16","first-page":"216","volume":"40","author":"J Si","year":"2017","unstructured":"Si, J., Mu, D., Sun, L., Qiao, Z., & Yang, K. (2017). Analysis and forecast of clinical decision support system for diabetes mellitus based on big data technique. International Journal of Biomedical Engineering, 40(3), 216\u2013220.","journal-title":"International Journal of Biomedical Engineering"},{"key":"1717_CR17","doi-asserted-by":"crossref","unstructured":"Gai, K., Qiu, M., Thuraisingham, B., & Tao, L. (2015). Proactive attribute-based secure data schema for mobile cloud in financial industry. 2015 IEEE 17th International Conference on High Performance Computing.","DOI":"10.1109\/HPCC-CSS-ICESS.2015.250"},{"key":"1717_CR18","unstructured":"Liu, M., Zhang, S., et al. (2012). State Estimation for Discrete-Time Chaotic Systems Based on a Unified Model.\u00a0IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics)."},{"key":"1717_CR19","doi-asserted-by":"publisher","first-page":"316","DOI":"10.1016\/j.jpdc.2017.11.001","volume":"118","author":"Z Lu","year":"2018","unstructured":"Lu, Z., Wang, N., et al. (2018). IoTDeM: An IoT Big Data-oriented MapReduce performance prediction extended model in multiple edge clouds. Journal of Parallel and Distributed Computing, 118, 316\u2013327.","journal-title":"Journal of Parallel and Distributed Computing"},{"key":"1717_CR20","doi-asserted-by":"crossref","unstructured":"Li, J., Qiu, M., Niu, J., et al. (2010) Feedback dynamic algorithms for preemptable job scheduling in cloud systems.\u00a0IEEE\/WIC\/ACM conf. on Web Intelligence.","DOI":"10.1109\/WI-IAT.2010.30"},{"key":"1717_CR21","unstructured":"Qiu, M., Khisamutdinov, E., Zhao, Z., Pan, C., Choi, J., Leontis, N., & Guo, P. (2013) RNA nanotechnology for computer design and in vivo computation.\u00a0Philosophical Transactions of the Royal Society A."},{"key":"1717_CR22","doi-asserted-by":"publisher","first-page":"766","DOI":"10.1016\/j.future.2015.05.005","volume":"56","author":"H Zhao","year":"2016","unstructured":"Zhao, H., Chen, M., et al. (2016). A novel pre-cache schema for high performance Android system. Future Generation Computer Systems, 56, 766\u2013772.","journal-title":"Future Generation Computer Systems"},{"key":"1717_CR23","doi-asserted-by":"crossref","unstructured":"Gai, K., Qiu, M., Sun, X., & Zhao, H. (2016). Security and privacy issues: A survey on FinTech.\u00a0International Conference on Smart Computing and Communication, 236\u2013247.","DOI":"10.1007\/978-3-319-52015-5_24"},{"issue":"8","key":"1717_CR24","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1109\/MCOM.2012.6257528","volume":"50","author":"H Su","year":"2012","unstructured":"Su, H., Qiu, M., & Wang, H. (2012). Secure wireless communication system for smart grid with rechargeable electric vehicles. IEEE Communications Magazine, 50(8), 62\u201368.","journal-title":"IEEE Communications Magazine"},{"key":"1717_CR25","doi-asserted-by":"crossref","unstructured":"Thakur, K., Qiu, M., Gaim K., & Ali, M. (2015). An investigation on cyber security threats and security models.\u00a0IEEE CSCloud.","DOI":"10.1109\/CSCloud.2015.71"},{"key":"1717_CR26","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Wu, J., et al. (2008). Jamming ACK attack to wireless networks and a mitigation approach. IEEE GLOBECOM Conference, 1-5.","DOI":"10.1109\/GLOCOM.2008.ECP.950"},{"key":"1717_CR27","doi-asserted-by":"crossref","unstructured":"Qiu, H., Qiu,\u00a0M., Memmi,\u00a0G., Ming,\u00a0Z., & Liu,\u00a0M. (2018). A dynamic scalable blockchain based communication architecture for IoT. International Conference on Smart Blockchain, 159-166.","DOI":"10.1007\/978-3-030-05764-0_17"},{"issue":"4","key":"1717_CR28","first-page":"274","volume":"28","author":"Q Che","year":"2020","unstructured":"Che, Q., Zheng, Q., Chen, Si., Ma, Y., Zhou, Z., Wu, Y., et al. (2020). The construction of predicting model for type 2 diabetes mellitus risk on the basis of artificial neural network approach. Chinese Journal of Prevention and Control of Chronic Diseases, 28(4), 274\u2013279.","journal-title":"Chinese Journal of Prevention and Control of Chronic Diseases"},{"key":"1717_CR29","unstructured":"Hou, Y., Zhu, Y., Zhu, L., Wu, S., & Gao, Q. (2016). Application of Decision Tree Model in Prediction of Type 2 Diabetes Risk. Chinese Journal of Health Statistics, 33(6), 976-978, 982."},{"key":"1717_CR30","unstructured":"Liu, Y., Sun, H., Zhang, Y., & Zhao, Z. (2018). Research on diabetes prediction model based on support vector machine. Journal of Harbin University of Commerce (Natural Sciences Edition), 34(1), 61-65, 74."},{"issue":"6","key":"1717_CR31","first-page":"560","volume":"18","author":"X Wang","year":"2010","unstructured":"Wang, X., & Chen, D. (2010). Application of Support Vector Machine on Predictive Model of Type 2 Diabetes. Chinese Journal of Prevention and Control of Chronic Non-Communicable Diseases, 18(6), 560\u2013562.","journal-title":"Chinese Journal of Prevention and Control of Chronic Non-Communicable Diseases"},{"key":"1717_CR32","unstructured":"Li, J., Wu, Q., & Li, S. (2014). Application of Data Mining Technology in Building a Risk Assessment Model of Type 2 Diabetes Mellitus. Journal of Gannan Medical University, (6), 974-977, 982."},{"issue":"9","key":"1717_CR33","first-page":"23","volume":"33","author":"X Liu","year":"2018","unstructured":"Liu, X., & Li, W. (2018). Study on Jump Volatility of Financial High-frequency Data: Based on the Method of Big-data Kernel Functions SVM. Statistics & Information Forum, 33(9), 23\u201330.","journal-title":"Statistics & Information Forum"},{"key":"1717_CR34","unstructured":"Feng, G. (2011). Parameter optimizing for Support Vector Machines classification. Computer Engineering and Applications, 47(3), 123-124,128."},{"key":"1717_CR35","first-page":"78","volume":"2","author":"College of Marine Science, Shanghai Ocean University","year":"2020","unstructured":"College of Marine Science, Shanghai Ocean University. (2020). Influence of different SVM kernel functions on the classification accuracy of GF-2 image in Nanhui tidal flat. Transactions of Oceanology and Limnology, 2, 78\u201389.","journal-title":"Transactions of Oceanology and Limnology"},{"issue":"11","key":"1717_CR36","first-page":"1483","volume":"38","author":"J Jiang","year":"2012","unstructured":"Jiang, J., He, Y., & Li, J. (2012). Modification of SVM\u2019s optimal hyperplane based on minimal mistake. Journal of Beijing University of Aeronautics and Astronautics, 38(11), 1483\u20131486.","journal-title":"Journal of Beijing University of Aeronautics and Astronautics"},{"issue":"2","key":"1717_CR37","first-page":"116","volume":"36","author":"A Mi","year":"2017","unstructured":"Mi, A., & Zhang, P. (2017). A method of classifier selection based on confusion matrix. Journal of Henan Polytechnic University (Natural Science), 36(2), 116\u2013121.","journal-title":"Journal of Henan Polytechnic University (Natural Science)"},{"key":"1717_CR38","unstructured":"Guo, Y., Guo, W., Qin, Y., He, Q., Zhang, X., & Wu, C. (2016). Consistency Check Based on Kappa Coefficient and Its Software Realization. Chinese Journal of Health Statistics, 33(1), 169-170, 174."},{"issue":"02","key":"1717_CR39","first-page":"175","volume":"16","author":"J Wang","year":"2008","unstructured":"Wang, J. (2008). Application of ROC curve in clinical medical diagnosis experiment. Chinese Journal of Hypertension, 16(02), 175\u2013177.","journal-title":"Chinese Journal of Hypertension"},{"key":"1717_CR40","doi-asserted-by":"crossref","unstructured":"Bradley, A. P. (1997). The use of the area under the ROC curve in the evaluation of machine learning algorithms. Patttern Recognition, 1145-1159.","DOI":"10.1016\/S0031-3203(96)00142-2"},{"issue":"2","key":"1717_CR41","first-page":"140","volume":"19","author":"M Ren","year":"2019","unstructured":"Ren, M., Sun, X., Wang, M., Huo, D., Li, Y., & Guo, L. (2019). Risk factors associated with prediabetes in Chinese: a meta-analysis. Chinese Journal of Evidence-Based Medicine, 19(2), 140\u2013146.","journal-title":"Chinese Journal of Evidence-Based Medicine"},{"issue":"11","key":"1717_CR42","first-page":"22","volume":"1","author":"H Jia","year":"2017","unstructured":"Jia, H., & Sun, Y. (2017). Analysis of the Prevalence and Related Factors of Prediabetes. Journal of Imaging Research and Medical Applications, 1(11), 22\u201323.","journal-title":"Journal of Imaging Research and Medical Applications"},{"issue":"7","key":"1717_CR43","first-page":"600","volume":"14","author":"X Meng","year":"2010","unstructured":"Meng, X., Yu, T., & Zhang, X. (2010). A case-control study on risk factors of type 2 diabetes mellitus. Chinese Journal of Disease Control & Prevention, 14(7), 600\u2013602.","journal-title":"Chinese Journal of Disease Control & Prevention"},{"key":"1717_CR44","unstructured":"Yang, M., Pu, K., & Li Z. (2016). Data Preprocessing of Diabetes Electronic Medical Records. Journal of Medical Intelligence, 37(5), 59-62, 84."},{"issue":"19","key":"1717_CR45","first-page":"76","volume":"44","author":"H Chen","year":"2008","unstructured":"Chen, H., Lin, L., Wang, J., & Miao, X. (2008). Data mining platform-WEKA and secondary development on WEKA. Computer Engineering and Applications, 44(19), 76\u201379.","journal-title":"Computer Engineering and Applications"},{"issue":"1","key":"1717_CR46","first-page":"1359","volume":"24","author":"S Chen","year":"2014","unstructured":"Chen, S., Luo, S., Pan, L., et al. (2014). Quantitative Influence of Risk Factors on Blood Glucose Level. Biomedical Materials and Engineering, 24(1), 1359\u20131366.","journal-title":"Biomedical Materials and Engineering"},{"issue":"4","key":"1717_CR47","first-page":"41","volume":"28","author":"X Lin","year":"2019","unstructured":"Lin, X., Li, J., Liu, L., Liang, C., & Ren, H. (2019). Risk prediction models of type 2 diabetic nephropathy. Chinese Journal of Medical Library and Information Science, 28(4), 41\u201345.","journal-title":"Chinese Journal of Medical Library and Information Science"},{"issue":"2","key":"1717_CR48","doi-asserted-by":"publisher","first-page":"728","DOI":"10.1109\/JBHI.2014.2325615","volume":"19","author":"L Han","year":"2015","unstructured":"Han, L., Luo, S., Yu, J., et al. (2015). Rule Extraction from Support Vector Machines Using Ensemble Learning Approach: An Application for Diagnosis of Diabetes. IEEE Journal of Biomedical and Health Informatics, 19(2), 728\u2013734.","journal-title":"IEEE Journal of Biomedical and Health Informatics"}],"container-title":["Journal of Signal Processing Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11265-021-01717-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11265-021-01717-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11265-021-01717-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,16]],"date-time":"2022-11-16T01:12:06Z","timestamp":1668561126000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11265-021-01717-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,19]]},"references-count":48,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2022,11]]}},"alternative-id":["1717"],"URL":"https:\/\/doi.org\/10.1007\/s11265-021-01717-4","relation":{},"ISSN":["1939-8018","1939-8115"],"issn-type":[{"type":"print","value":"1939-8018"},{"type":"electronic","value":"1939-8115"}],"subject":[],"published":{"date-parts":[[2021,11,19]]},"assertion":[{"value":"18 September 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 October 2021","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 October 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 November 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}