請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/56725完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 歐陽彥正 | |
| dc.contributor.author | Pin-Liang Chen | en |
| dc.contributor.author | 陳品良 | zh_TW |
| dc.date.accessioned | 2021-06-16T05:44:32Z | - |
| dc.date.available | 2019-08-16 | |
| dc.date.copyright | 2014-08-16 | |
| dc.date.issued | 2014 | |
| dc.date.submitted | 2014-08-11 | |
| dc.identifier.citation | [1] N. Aberg, 'Birth season variation in asthma and allergic rhinitis,' Clin Exp Allergy, vol. 19, pp. 643-8, 1989.
[2] D. Teilum, K. D. Bjerre, A. M. Tjonneland, and N. Kroman, 'Breast cancer survival and season of surgery: an ecological open cohort study,' BMJ Open, vol. 2, p. e000358, 2012. [3] A. C. Yang, N. E. Huang, C.-K. Peng, and S.-J. Tsai, 'Do seasons have an influence on the incidence of depression? The use of an internet search engine query data as a proxy of human affect,' PLoS ONE, vol. 5, p. e13728, 2010. [4] P. V. Targonski, V. W. Persky, and V. Ramekrishnan, 'Effect of environmental molds on risk of death from asthma during the pollen season,' J Allergy Clin Immunol, vol. 95, pp. 955-61, 1995. [5] C. Moller, S. Dreborg, H. A. Ferdousi, S. Halken, A. Host, L. Jacobsen, et al., 'Pollen immunotherapy reduces the development of asthma in children with seasonal rhinoconjunctivitis (the PAT-study),' J Allergy Clin Immunol, vol. 109, pp. 251-6, 2002. [6] J. H. V. Zeijl, R. A. Mullaart, G. F. Borm, and J. M. D. Galama, 'Recurrence of febrile seizures in the respiratory season is associated with influenza A,' J Pediatr, vol. 145, pp. 800-5, 2004. [7] S. Giaconi, S. Ghione, C. Palombo, A. Genovesi-Ebert, C. Marabotti, E. Fommei, et al., 'Seasonal influences on blood pressure in high normal to mild hypertensive range,' Hypertension, vol. 14, pp. 22-7, 1989. [8] P. J. Brennan, G. Greenberg, W. E. Miall, and S. G. Thompson, 'Seasonal variation in arterial blood pressure,' Br Med J, vol. 285, pp. 919-23, 1982. [9] T. Hata, T. Ogihara, A. Maruyama, H. Mikami, M. Nakamaru, T. Naka, et al., 'The seasonal variation of blood pressure in patients with essential hypertension,' Clin Exp Hypertens A, vol. 4, pp. 341-54, 1982. [10] Y. Y. Al-Tamer, J. M. T. Al-Hayali, and E. A. H. Al-Ramadhan, 'Seasonality of hypertension,' J Clin Hypertens (Greenwich), vol. 10, pp. 125-9, 2008. [11] S. Baxendale, 'Seeing the light? Seizures and sunlight,' Epilepsy Research, vol. 84, pp. 72-6, 2009. [12] M.-F. He, J.-L. Chen, S.-H. Liu, J.-S. Xu, Z.-R. Liang, S.-F. Li, et al., 'Investigation on the relationship between the solar term of onset and syndrome types in 430 patients with acute myocardial infarction by circular statistical analysis,' Chin Crit Care Med, vol. 22, pp. 693-5, 2010. [13] M. He, Z. Liang, J. Zhang, Z. Gao, S. Mo, Y. Zhang, et al., 'Solar term peak of onset and death in 1597 patients with acute ischemic stroke : circular statistical analysis,' Neural Regeneration Research, vol. 2, pp. 532-5, 2007. [14] N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, Q. Zheng, et al., 'The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis,' Proc. R. Soc. London, Ser. A, vol. 454, pp. 903-95, 1998. [15] N. E. Huang and Z. Wu, 'A review on Hilbert-Huang transform: Method and its applications to geophysical studies,' Reviews of Geophysics, vol. 46, p. 23, 2008. [16] OEMR. Available: http://www.oemr.org/ [17] OpenEMR. Available: http://www.open-emr.org/ [18] openEHR. Available: http://www.openehr.org/ [19] OpenMRS. Available: http://openmrs.org/ [20] C. Qian, Z.-W. Yan, and C.-B. Fu, 'Climatic changes in the twenty-four solar terms during 1960-2008,' Chinese Science Bulletin, vol. 57, pp. 276-86, 2012. [21] R. B. Cleveland, W. S. Cleveland, J. E. McRae, and I. Terpenning, 'STL: A seasonal-trend decomposition procedure based on loess,' Journal of Official Statistics, vol. 6, pp. 3-73, 1990. [22] W. S. Cleveland and S. J. Devlin, 'Locally-weighted regression: an approach to regression analysis by local fitting,' Journal of the American Statistical Association, vol. 83, pp. 596-610, 1988. [23] W. S. Cleveland, S. J. Devlin, and E. Grosse, 'Regression by local fitting: Methods, properties, and computational algorithms,' Journal of Econometrics, vol. 37, pp. 87-114, 1988. [24] N. E. Huang, M.-L. C. Wu, S. R. Long, S. S. P. Shen, W. Qu, P. Gloersen, et al., 'A confidence limit for the position empirical mode decomposition and Hilbert spectral analysis,' Proc. R. Soc. London, Ser. A, vol. 459, pp. 2317-45, 2003. [25] N. E. Huang, S. R. Long, and Z. Shen, 'The mechanism for frequency downshift in nonlinear wave evolution,' Advances in Applied Mechanics, vol. 32, pp. 59-111, 1996. [26] N. E. Huang, Z. Shen, and S. R. Long, 'A new view of nonlinear water waves: the Hilbert spectrum,' Annual Review of Fluid Mechanics, vol. 31, pp. 417-57, 1999. [27] Z. Wu and N. E. Huang, 'Ensemble empirical mode decomposition: a noise-assisted data analysis method,' Adv. Adapt. Data Anal., vol. 1, pp. 1-41, 2009. [28] P. Qin, Y. Lin, and M. Chen, 'Empirical mode decomposition method based on wavelet with translation invariance,' EURASIP Journal on Advances in Signal Processing, 2008. [29] D. Ren, S. Yang, Z. Wu, and G. Yan, 'Evaluation of the EMD end effect and a window based method to improve EMD,' presented at the International Technology and Innovation Conference, Hangzhou, 2006. [30] N. Rehman and D. P. Mandic, 'Multivariate empirical mode decomposition,' in Proc. Royal Soc. A, 2010, pp. 1291-302. [31] G. Rilling, P. Flandrin, and J. M. Lilly, 'Bivariate empirical mode decomposition,' IEEE Signal Processing Letters, vol. 14, pp. 936-9, 2007. [32] T. Tanaka and D. P. Mandic, 'Complex empirical mode decomposition,' IEEE Signal Processing Letters, vol. 14, pp. 101-4, 2007. [33] M. U. B. Altaf, T. Gautama, T. Tanaka, and D. P. Mandic1, 'Rotation invariant complex empirical mode decomposition,' presented at the IEEE International Conference on Acoustics, Speech and Signal Processing, 2007. [34] J. C. Nunes, O. Niang, Y. Bouaoune, E. Delechelle, and P. Bunel, 'Bidimensional empirical mode decomposition modified for texture analysis,' in Image Analysis: 13th Scandinavian Conference, Halmstad, Sweden, 2003, pp. 295-6. [35] N. E. Huang, 'Computer implemented empirical mode decomposition apparatus, method and article of manufacture for two-dimensional signals,' U.S. Patent, 2001. [36] J. C. Nunes, Y. Bouaoune, E. Delechelle, O. Niang, and P. Bunel, 'Image analysis by bidimensional empirical mode decomposition,' Image Vis. Comput., vol. 21, pp. 1019-26, 2003. [37] J. C. Nunes, S. Guyot, and E. Delechelle, 'Texture analysis based on local analysis of the bidimensional empirical mode decomposition,' Mach. Vis. Appl., vol. 16, pp. 177-88, 2005. [38] A. Linderhed, 'Variable sampling of the empirical mode decomposition of two-dimensional signals,' in Int. J. Wavelets Multresolut. Inf. Process., Linkoping, Sweden, 2005, pp. 435-52. [39] N.-F. Chang, T.-C. Chen, C.-Y. Chiang, and L.-G. Chen, 'On-line empirical mode decomposition biomedical microprocessor for Hilbert Huang transform,' presented at the BioCAS, 2011. [40] T. A. C. M. Claasen and W. F. G. Mecklenbrauker, 'The Wigner distribution: a tool for time-frequency signal analysis,' Philips J. Research, vol. 35, pp. 217-389, 1980. [41] L. Cohen, Time-frequency analysis. Englewood Cliffs, NJ: Prentice-Hall, 1995. [42] M. B. Priestley, 'Evolutionary spectra and non-stationary processes,' J. R. Statist. Soc. B, vol. 27, pp. 204-37, 1965. [43] R. Vautard and M. Ghil, 'Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series,' Physica D, vol. 35, pp. 395-424, 1989. [44] D. T.-H. Chang, Y.-J. Oyang, and J.-H. Lin, 'MEDock: a web server for efficient prediction of ligand binding sites based on a novel optimization algorithm,' Nucleic Acids Research, vol. 33, pp. W233-W238, 2005. [45] J. H. Holland, Adaptation in natural and artificial systems: an introductory analysis with applications to biology, control, and artificial intelligence: 1st MIT Press ed. Cambridge, 1990. [46] D. E. Clark, Evolutionary algorithms in molecular design. Weinheim, New York: Wiley-VCH, 2000. [47] C.-H. Hsieh, D. T.-H. Chang, and Y.-J. Oyang, 'Data classification with a generalized gaussian components based density estimation algorithm,' International Joint Conference on Neural Networks, pp. 1259-66, 2009. [48] G. M. Morris, D. S. Goodsell, R. S. Halliday, R. Huey, W. E. Hart, R. K. Belew, et al., 'Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function,' J. Comput. Chem., vol. 19, pp. 1639-62, 1998. [49] National Health Insurance Research Database. Available: http://nhird.nhri.org.tw/ [50] National Health Insurance. Available: http://www.nhi.gov.tw/ [51] Ninth Edition of the International Classification of Diseases' Clinical Modification. Available: http://icd9cm.chrisendres.com/ [52] P.-L. Chen, W.-J. Lee, W.-Z. Sun, Y.-J. Oyang, and J.-L. Fuh, 'Risk of dementia in patients with insomnia and long-term use of hypnotics: a population-based retrospective cohort study,' PLoS ONE, vol. 7, p. e49113, 2012. [53] P.-L. Chen, C.-W. Yang, Y.-K. Tseng, W.-Z. Sun, J.-L. Wang, S.-J. Wang, et al., 'Risk of dementia after anaesthesia and surgery,' British Journal of Psychiatry, vol. 204, pp. 188-93, 2013. [54] D.-D. Lee, C.-K. Huang, P.-C. Ko, Y.-T. Chang, W.-Z. Sun, and Y.-J. Oyang, 'Association of primary cutaneous amyloidosis with atopic dermatitis: a nationwide population-based study in Taiwan,' Br J Dermatol, vol. 164, pp. 148-53, Jan 2011. [55] M.-H. Yang, P.-H. Wang, S.-J. Wang, W.-Z. Sun, Y.-J. Oyang, and J.-L. Fuh, 'Women with endometriosis are more likely to suffer from migraines: a population-based study,' PLoS ONE, vol. 7, p. e33941, 2012. [56] M.-H. Yang, F.-Y. Yang, and Y.-J. Oyang, 'Application of density estimation algorithms in analyzing co-morbidities of migraine,' Network Modeling Analysis in Health Informatics and Bioinformatics, 2013. [57] N. Sprem and S. Branica, 'Effect of climatic elements on the frequency of secretory otitis media,' Eur Arch Otorhinolaryngol, vol. 250, pp. 286-8, 1993. [58] A. Yildirim, H. Erdem, S. Kilic, S. Yetiser, and A. Pahsa, 'Effect of climate on the bacteriology of chronic suppurative otitis media,' Ann Otol Rhinol Laryngol, vol. 114, pp. 652-5, 2005. [59] R. d. Marco, A. Poli, M. Ferrari, S. Accordini, G. Giammanco, M. Bugiani, et al., 'The impact of climate and traffic-related NO2 on the prevalence of asthma and allergic rhinitis in Italy,' Clin Exp Allergy, vol. 32, pp. 1405-12, 2002. [60] M. E. Zanolin, C. Pattaro, A. Corsico, M. Bugiani, L. Carrozzi, L. Casali, et al., 'The role of climate on the geographic variability of asthma, allergic rhinitis and respiratory symptoms: results from the Italian study of asthma in young adults,' Allergy, vol. 59, pp. 306-14, 2004. [61] S. K. Weiland, A. Hu‥sing, D. P. Strachan, P. Rzehak, and N. Pearce, 'Climate and the prevalence of symptoms of asthma, allergic rhinitis, and atopic eczema in children,' Occup Environ Med, vol. 61, pp. 609-15, 2004. [62] Y.-L. Lee, C.-K. Shawz, H.-J. Su, J.-S. Lai, Y.-C. Ko, S.-L. Huang, et al., 'Climate, traffic-related air pollutants and allergic rhinitis prevalence in middle-school children in Taiwan,' Eur Respir J, vol. 21, pp. 964-70, 2003. [63] Y.-K. Chen, H.-C. Lin, C.-S. Chen, and S.-D. Yeh, 'Seasonal variations in urinary calculi attacks and their association with climate: a population based study,' J Urol, vol. 179, pp. 564-9, 2008. [64] F. Hussain, F. R. Billimoria, and P. P. Singh, 'Urolithiasis in northeast Bombay: seasonal prevalence and chemical composition of stones,' Int Urol Nephrol, vol. 22, pp. 119-24, 1990. [65] R. A. Tupker, P. J. Coenraads, V. Fidler, M. C. D. Jong, J. B. V. d. Meer, and J. G. D. Monchy, 'Irritant susceptibility and weal and flare reactions to bioactive agents in atopic dermatitis,' British Journal of Dermatology, vol. 133, pp. 365-70, 1995. [66] G. Byremo, G. Rod, and K. H. Carlsen, 'Effect of climatic change in children with atopic eczema,' Allergy, vol. 61, pp. 1403-10, 2006. [67] K. Wallis, G. Akers, P. Collins, R. Davis, A. Frazier, M. Oxley, et al., 'Complex empirical mode decomposition, Hilbert-Huang transform, and fourier transform applied to moving objects,' presented at the IEEE IGARSS, 2012. [68] P. Masset, 'Analysis of financial time-series using Fourier and wavelet methods,' Social Science Research Network, 2008. [69] D. Labate, F. L. Foresta, G. Occhiuto, F. C. Morabito, A. Lay-Ekuakille, and a. P. Vergallo, 'Empirical mode decomposition vs. wavelet decomposition for the extraction of respiratory signal from single-channel ECG: a comparison,' IEEE Sensors Journal, vol. 13, pp. 2666-74, 2013. [70] A. Amar and Z. E. a. Guennoun, 'Contribution of wavelet transformation and empirical mode decomposition to measurement of U.S core inflation,' Applied Mathematical Sciences, vol. 6, pp. 6739-52, 2012. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/56725 | - |
| dc.description.abstract | 近年來，大型臨床醫學資料庫的研究越來越受到關注。傳統的統計與時間序列分析方法經常被使用，但都有其侷限性。因此，發展一個更好的時間序列分析法是必須的。本論文中，我們發展了傅立葉－高斯分解方法，利用傅立葉轉換、高斯函數與一個最佳化演算法，可將一個訊號分解出數個具有不同代表意義的趨勢。傅立葉－高斯分解法可萃取出一個訊號中具有相同頻率的不同趨勢，這是其他方法所做不到的。此外，我們將傅立葉－高斯分解法應用在分析台灣全民健康保險研究資料庫的疾病及到院前心肺功能停止資料庫，並且得到了一些有趣的發現。我們在過敏性鼻炎、氣喘、急性心肌梗塞的看病人次中找到了特殊的趨勢。過敏性鼻炎的看病人次在每年的三月和十一月達到最高峰；氣喘的看病人次在四月和十一月達到最高峰；急性心肌梗塞的看病人次則是在在立春、立夏、立冬達到最高峰。此外，我們發現循環系統疾病與消化系統疾病的看病人次有相同的趨勢。它們都在春分、芒種、冬至大幅下降。在到院前心肺功能停止資料庫中，我們發現非創傷性到院前心肺功能停止的病患人數在冬天大幅增加而夏天小幅度增加。非創傷性到院前心肺功能停止病患的存活率則在春天與秋天上升，與病患人數呈現相反的趨勢。 | zh_TW |
| dc.description.abstract | In recent years, more and more studies have focused on the large medical databases. Traditional statistical approaches and time series analysis methods are frequently used, but they have some limitations. Therefore, to develop an advanced time series analysis method is required. In this thesis, we develop the Fourier-Gaussian decomposition method and show that it can decompose a signal into a finite and small number of components. Fourier-Gaussian decomposition can extract different components with the same frequency from a signal, which is not available in other methods. Furthermore, we apply Fourier-Gaussian decomposition to analyze several diseases in Taiwan’s National Health Insurance Research Database (NHIRD) and the out of hospital cardiac arrest (OHCA) database. Finally, we get some interesting findings. We find special patterns in allergic rhinitis visits, asthma visits, and AMI visits. Allergic rhinitis visits contained one-year period and peaked in March and November; asthma visits peaked in April and November; AMI visits peaked in Spring Begins, Summer Begins and Winter Begins. Besides, we find that circulatory system diseases visits and digestive system diseases visits have the same pattern. The number of patients decreased rapidly at Vernal Equinox, Grain in Ear and Winter Solstice. In OHCA database, we find that the number of non-traumatic OHCA patients increased rapidly in winter and slightly in summer. The survival rate of non-traumatic OHCA patients increased in spring and autumn, which is reverse to the number of non-traumatic OHCA patients. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T05:44:32Z (GMT). No. of bitstreams: 1 ntu-103-D97922006-1.pdf: 1287800 bytes, checksum: 09e17bbeab5df75c52629ac9d8b4b14d (MD5) Previous issue date: 2014 | en |
| dc.description.tableofcontents | 致謝 i
摘要 ii Abstract iv Contents vi List of Tables viii List of Figures ix Chapter 1 Introduction 1 1.1 Motivation 1 1.1.1 Development of time series analysis 2 1.1.2 Electronic health record systems 3 1.1.3 Analysis on different time scales 4 1.2 Contribution 5 1.3 Organization 5 Chapter 2 Background 8 2.1 Time series analysis methods 8 2.1.1 Fourier transform 8 2.1.2 Wavelet transform 9 2.1.3 STL 10 2.1.4 Hilbert-Huang transform 11 2.1.5 Other methods 13 2.2 Rank-based adaptive mutation evolutionary algorithm 14 Chapter 3 The Medical Databases 19 3.1 National Health Insurance Research Database 19 3.2 Study samples 21 3.3 Out of Hospital Cardiac Arrest database 23 3.4 Study samples of OHCA database 23 Chapter 4 Fourier-Gaussian Decomposition Methods 26 4.1 The first phase of the FGD algorithm 26 4.2 The second phase of the FGD algorithm 29 4.3 Comparison with other decomposition methods 36 4.4 Strengths and Limitations 36 Chapter 5 Analysis of Medical Databases 40 5.1 Mental disorders 41 5.2 Diseases of the sense organs 41 5.3 Diseases of the respiratory system 42 5.4 Diseases of the circulatory system 43 5.5 Diseases of the digestive system 45 5.6 Diseases of the genitourinary system 47 5.7 Diseases of the skin and subcutaneous tissue 48 5.8 Out of hospital cardiac arrest 49 Chapter 6 Discussion and Conclusion 69 6.1 Discussion 69 6.2 Conclusion 70 6.3 Future work 71 References 72 | |
| dc.language.iso | en | |
| dc.subject | 傅立葉－高斯分解法 | zh_TW |
| dc.subject | 時間序列分析 | zh_TW |
| dc.subject | 全民健康保險研究資料庫 | zh_TW |
| dc.subject | 到院前心肺功能停止資料庫 | zh_TW |
| dc.subject | 高斯函數 | zh_TW |
| dc.subject | 傅立葉轉換 | zh_TW |
| dc.subject | time series analysis | en |
| dc.subject | Gaussian function | en |
| dc.subject | Fourier-Gaussian decomposition | en |
| dc.subject | NHIRD | en |
| dc.subject | OHCA database | en |
| dc.subject | Fourier transform | en |
| dc.title | 一個新的時間序列分析法及其在大型醫學資料庫的應用 | zh_TW |
| dc.title | A New Time Series Analysis Method and its Application in Analysis of Large Medical Databases | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 102-2 | |
| dc.description.degree | 博士 | |
| dc.contributor.oralexamcommittee | 黃乾綱,陳倩瑜,趙坤茂,孫維仁 | |
| dc.subject.keyword | 傅立葉轉換,高斯函數,傅立葉－高斯分解法,全民健康保險研究資料庫,到院前心肺功能停止資料庫,時間序列分析, | zh_TW |
| dc.subject.keyword | Fourier transform,Gaussian function,Fourier-Gaussian decomposition,NHIRD,OHCA database,time series analysis, | en |
| dc.relation.page | 95 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2014-08-11 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
文件中的檔案：
| 檔案 | 大小 | 格式 | |
|---|---|---|---|
| ntu-103-1.pdf 未授權公開取用 | 1.26 MB | Adobe PDF |
系統中的文件，除了特別指名其著作權條款之外，均受到著作權保護，並且保留所有的權利。