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智慧健康研究综述: 从云端到边缘的系统(15)
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摘要:[13]Fan Lu, Buchanan W, Thummler C, et al. DACAR platform for eHealth services cloud[C] //Proc of the 4th IEEE Int Conf on Cloud Computing. Piscataway, NJ: IEEE, 2011: 219-226 [14]Chen Min, Mao Shiwen
[13]Fan Lu, Buchanan W, Thummler C, et al. DACAR platform for eHealth services cloud[C] //Proc of the 4th IEEE Int Conf on Cloud Computing. Piscataway, NJ: IEEE, 2011: 219-226
[14]Chen Min, Mao Shiwen, Liu Yunhao. Big data: A survey[J]. Mobile Networks and Applications, 2014, 19(2): 171-209
[15]White T. Hadoop: The Definitive Guide[M]. Sebastopol, CA: O’Reilly Media, 2012: 45-48
[16]Natarajan K, Stein D, Jain S, et al. An analysis of clinical queries in an electronic health record search utility[J]. International Journal of Medical Informatics, 2010, 79(7): 515-522
[17]Yang Lei, Mei Qiaozhu, Zheng Kai, et al. Query log analysis of an electronic health record search engine[C] //Proc of the American Medical Informatics Association Annual Symp. Bethesda, MD: AMIA, 2011: 915-924
[18]Mu Xiangming, Lu Kun. Towards effective genomic information retrieval: The impact of query complexity and expansion strategies[J]. Journal of Information Science, 2010, 36(2): 194-208
[19]Yang Yang. Attribute-based data retrieval with semantic keyword search for e-health cloud[J]. Journal of Cloud Computing, 2015, 4(1): 10-16
[20]Zhang Lili, Zhang Yuqing, Liu Xuefeng, et al. Efficient conjunctive keyword search over encrypted electronic medical records[J]. Journal of Software, 2016, 27(6): 1577-1591 (in Chinese)(张丽丽, 张玉清, 刘雪峰, 等. 对加密电子医疗记录有效的连接关键词的搜索[J]. 软件学报, 2016, 27(6): 1577-1591)
[21]Yang Liu, Jin Rong, Mummert L, et al. A boosting framework for visuality-preserving distance metric learning and its application to medical image retrieval[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2010, 32(1): 30-44
[22]Rahman M M, Bhattacharya P, Desai B C. A framework for medical image retrieval using machine learning and statistical similarity matching techniques with relevance feedback[J]. IEEE Transactions on Information Technology in Biomedicine, 2007, 11(1): 58-69
[23]Cabarcos A, Sanchez T, Seoane J A, et al. Retrieval and management of medical information from heterogeneous sources, for its integration in a medical record visualisation tool[J]. International Journal of Electronic Healthcare, 2010, 5(4): 371-385
[24]Kim J, Feng Dagan, Cai Wendong, et al. Integrated multimedia medical data agent in e-Health[C] //Proc of the Pan-Sydney Area Workshop on Visual Information. Darlinghurst, SYD: Australian Computer Society, 2001:11-15
[25]Shen Chiaping, Chen Weihsin, Chen Jiaming, et al. Bio-signal analysis system design with support vector machines based on cloud computing service architecture[C] //Proc of the Annual Int Conf of the IEEE Engineering in Medicine and Biology. Piscataway, NJ: IEEE, 2010: 1421-1424
[26]Takeuchi H, Kodama N. Validity of association rules extracted by healthcare-data-mining[C] //Proc of the 36th Annual Int Conf of the IEEE Engineering in Medicine and Biology Society. Piscataway, NJ: IEEE, 2014: 4960-4963
[27]Kurt I, Ture M, Kurum A T. Comparing performances of logistic regression, classification and regression tree, and neural networks for predicting coronary artery disease[J]. Expert Systems with Applications, 2008, 34(1): 366-374
[28]Nkosi M T, Mekuria F. Cloud computing for enhanced mobile health applications[C] //Proc of the 2nd IEEE Int Conf on Cloud Computing Technology and Science. Piscataway, NJ: IEEE, 2010: 629-633
[29]Wang Xiaoliang, Gui Qiong, Liu Bingwei, et al. Enabling smart personalized healthcare: A hybrid mobile-cloud approach for ECG telemonitoring[J]. IEEE Journal of Biomedical and Health Informatics, 2014, 18(3): 739-745
[30]Hsieh J, Hsu M W. A cloud computing based 12-lead ECG telemedicine service[J]. BMC Medical Informatics and Decision Making, 2012, 12(1): 77-88
[31]Parkka J, Ermes M, Korpipaa P, et al. Activity classification using realistic data from wearable sensors[J]. IEEE Transactions on Information Technology in Biomedicine, 2006, 10(1): 119-128
[32]Leonov V. Thermoelectric energy harvesting of human body heat for wearable sensors[J]. IEEE Sensors Journal, 2013, 13(6): 2284-2291
[33]Poon C C Y, Zhang Yuanting. Cuff-less and noninvasive measurements of arterial blood pressure by pulse transit time[C] //Proc of the 27th IEEE Annual Conf Engineering in Medicine and Biology. Piscataway, NJ: IEEE, 2006: 5877-5880
[34]Tamura T, Maeda Y, Sekine M, et al. Wearable photoplethysmographic sensors—Past and present[J]. Electronics, 2014, 3(2): 282-302
[35]Baek H J, Chung G S, Kim K K, et al. Photoplethys-mography measurement without direct skin-to-sensor contact using an adaptive light source intensity control[J]. IEEE Transactions on Information Technology in Biomedicine, 2009, 13(6): 1085-1088
[36]Poh M Z, McDuff D J, Picard R W. Advancements in noncontact, multiparameter physiological measurements using a webcam[J]. IEEE Transactions on Biomedical Engineering, 2011, 58(1): 7-11
[37]Baek H J, Chung G S, Kim K K, et al. A smart health monitoring chair for nonintrusive measurement of biological signals[J]. IEEE Transactions on Information Technology in Biomedicine, 2012, 16(1): 150-158
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