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2022 | OriginalPaper | Buchkapitel

11. Healthcare Applications

verfasst von : Yong Shi

Erschienen in: Advances in Big Data Analytics

Verlag: Springer Nature Singapore

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Abstract

Healthcare is also a very hot application area of data science, especially in the COVID-19 pandemic around the world since the beginning of 2020. This chapter provides two sections of the related healthcare applications. Section 11.1 deals with the evaluation of medical doctor’s performance by using ordinal regression-based approach [1], while Sect. 11.2 outlines a cutting-edge research finding to learn transmission patterns of COVID-19 outbreak by using an age-specific social contact characterization [2].

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Literatur
1.
Zurück zum Zitat Shi, Y., Li, P., Yu, X., Wang, H., Niu, L.: Evaluating doctor performance: ordinal regression-based approach. J. Med. Internet Res. 20(7), e240 (2018)CrossRef Shi, Y., Li, P., Yu, X., Wang, H., Niu, L.: Evaluating doctor performance: ordinal regression-based approach. J. Med. Internet Res. 20(7), e240 (2018)CrossRef
2.
Zurück zum Zitat Liu, Y., Gu, Z., Xia, S., Shi, B., Zhou, X.N., Shi, Y., Liu, J.: What are the underlying transmission patterns of covid-19 outbreak? An age-specific social contact characterization. EClinicalMedicine. 22, 100354 (2020)CrossRef Liu, Y., Gu, Z., Xia, S., Shi, B., Zhou, X.N., Shi, Y., Liu, J.: What are the underlying transmission patterns of covid-19 outbreak? An age-specific social contact characterization. EClinicalMedicine. 22, 100354 (2020)CrossRef
3.
Zurück zum Zitat Hsieh, C.J., Chang, K.W., Lin, C.J., Keerthi, S.S., Sundararajan, S.: A dual coordinate descent method for large-scale linear svm. In: Proceedings of the 25th International Conference on Machine Learning, pp. 408–415 (2008)CrossRef Hsieh, C.J., Chang, K.W., Lin, C.J., Keerthi, S.S., Sundararajan, S.: A dual coordinate descent method for large-scale linear svm. In: Proceedings of the 25th International Conference on Machine Learning, pp. 408–415 (2008)CrossRef
4.
Zurück zum Zitat Xue, N.: Chinese word segmentation as character tagging. Int. J. Computat. Linguist. Chin. Lang. Process. 8(1) (2003) Special Issue on Word Formation and Chinese Language Processing, 29–48 (2003) Xue, N.: Chinese word segmentation as character tagging. Int. J. Computat. Linguist. Chin. Lang. Process. 8(1) (2003) Special Issue on Word Formation and Chinese Language Processing, 29–48 (2003)
5.
Zurück zum Zitat Zhang, Y., Jin, R., Zhou, Z.H.: Understanding bag-of-words model: a statistical framework. Int. J. Mach. Learn. Cybern. 1(1–4), 43–52 (2010)CrossRef Zhang, Y., Jin, R., Zhou, Z.H.: Understanding bag-of-words model: a statistical framework. Int. J. Mach. Learn. Cybern. 1(1–4), 43–52 (2010)CrossRef
6.
Zurück zum Zitat Witten, I.H., Frank, E.: Data mining: practical machine learning tools and techniques with java implementations. ACM SIGMOD Rec. 31(1), 76–77 (2002)CrossRef Witten, I.H., Frank, E.: Data mining: practical machine learning tools and techniques with java implementations. ACM SIGMOD Rec. 31(1), 76–77 (2002)CrossRef
7.
Zurück zum Zitat Friedman, J.H.: Greedy function approximation: a gradient boosting machine. Ann. Stat. 2001, 1189–1232 (2001)MathSciNetMATH Friedman, J.H.: Greedy function approximation: a gradient boosting machine. Ann. Stat. 2001, 1189–1232 (2001)MathSciNetMATH
8.
Zurück zum Zitat Chapelle, O., Shivaswamy, P., Vadrevu, S., Weinberger, K., Zhang, Y., Tseng, B.: Multi-task learning for boosting with application to web search ranking. In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1189–1198 (2010)CrossRef Chapelle, O., Shivaswamy, P., Vadrevu, S., Weinberger, K., Zhang, Y., Tseng, B.: Multi-task learning for boosting with application to web search ranking. In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 1189–1198 (2010)CrossRef
9.
Zurück zum Zitat Kramer, S., Widmer, G., Pfahringer, B., De Groeve, M.: Prediction of ordinal classes using regression trees. Fundam. Inform. 47(1–2), 1–13 (2001)MathSciNetMATH Kramer, S., Widmer, G., Pfahringer, B., De Groeve, M.: Prediction of ordinal classes using regression trees. Fundam. Inform. 47(1–2), 1–13 (2001)MathSciNetMATH
10.
Zurück zum Zitat Chu, W., Keerthi, S.S.: New approaches to support vector ordinal regression. In: Proceedings of the 22nd International Conference on Machine Learning, pp. 145–152 (2005)CrossRef Chu, W., Keerthi, S.S.: New approaches to support vector ordinal regression. In: Proceedings of the 22nd International Conference on Machine Learning, pp. 145–152 (2005)CrossRef
12.
Zurück zum Zitat Gu, B., Sheng, V.S., Tay, K.Y., Romano, W., Li, S.: Incremental support vector learning for ordinal regression. IEEE Trans. Neural Netw. Learn. Syst. 26(7), 1403–1416 (2014)MathSciNetCrossRef Gu, B., Sheng, V.S., Tay, K.Y., Romano, W., Li, S.: Incremental support vector learning for ordinal regression. IEEE Trans. Neural Netw. Learn. Syst. 26(7), 1403–1416 (2014)MathSciNetCrossRef
13.
Zurück zum Zitat Herbrich, R., Graepel, T., Obermayer, K.: Support vector learning for ordinal regression (1999) Herbrich, R., Graepel, T., Obermayer, K.: Support vector learning for ordinal regression (1999)
14.
Zurück zum Zitat Frank, E., Hall, M.: A simple approach to ordinal classification. In: European Conference on Machine Learning, pp. 145–156 (2001) Frank, E., Hall, M.: A simple approach to ordinal classification. In: European Conference on Machine Learning, pp. 145–156 (2001)
15.
Zurück zum Zitat Waegeman, W., Boullart, L.: An ensemble of weighted support vector machines for ordinal regression. Int. J. Comput. Syst. Sci. Eng. 3(1), 47–51 (2009) Waegeman, W., Boullart, L.: An ensemble of weighted support vector machines for ordinal regression. Int. J. Comput. Syst. Sci. Eng. 3(1), 47–51 (2009)
16.
Zurück zum Zitat Gutiérrez, P.A., Perez-Ortiz, M., Sanchez-Monedero, J., Fernandez-Navarro, F., Hervas-Martinez, C.: Ordinal regression methods: survey and experimental study. IEEE Trans. Knowl. Data Eng. 28(1), 127–146 (2015)CrossRef Gutiérrez, P.A., Perez-Ortiz, M., Sanchez-Monedero, J., Fernandez-Navarro, F., Hervas-Martinez, C.: Ordinal regression methods: survey and experimental study. IEEE Trans. Knowl. Data Eng. 28(1), 127–146 (2015)CrossRef
17.
Zurück zum Zitat Cardoso, J., da Costa, J.P.: Learning to classify ordinal data: the data replication method. J. Mach. Learn. Res. 8, 1393–1429 (2007)MathSciNetMATH Cardoso, J., da Costa, J.P.: Learning to classify ordinal data: the data replication method. J. Mach. Learn. Res. 8, 1393–1429 (2007)MathSciNetMATH
18.
Zurück zum Zitat Gutiérrez, P.A., Pérez-Ortiz, M., Fernández-Navarro, F., Sánchez-Monedero, J., Hervás-Martínez, C.: An experimental study of different ordinal regression methods and measures. In: International Conference on Hybrid Artificial Intelligence Systems, pp. 296–307 (2012) Gutiérrez, P.A., Pérez-Ortiz, M., Fernández-Navarro, F., Sánchez-Monedero, J., Hervás-Martínez, C.: An experimental study of different ordinal regression methods and measures. In: International Conference on Hybrid Artificial Intelligence Systems, pp. 296–307 (2012)
19.
Zurück zum Zitat Diao, Q., Qiu, M., Wu, C.Y., Smola, A.J., Jiang, J., Wang, C.: Jointly modeling aspects, ratings and sentiments for movie recommendation (jmars). In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 193–202 (2014)CrossRef Diao, Q., Qiu, M., Wu, C.Y., Smola, A.J., Jiang, J., Wang, C.: Jointly modeling aspects, ratings and sentiments for movie recommendation (jmars). In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 193–202 (2014)CrossRef
20.
Zurück zum Zitat Shimada, K., Endo, T.: Seeing several stars: a rating inference task for a document containing several evaluation criteria. In: Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 1006–1014 (2008)CrossRef Shimada, K., Endo, T.: Seeing several stars: a rating inference task for a document containing several evaluation criteria. In: Pacific-Asia Conference on Knowledge Discovery and Data Mining, pp. 1006–1014 (2008)CrossRef
21.
Zurück zum Zitat Tang, D., Qin, B., Liu, T.: Document modeling with gated recurrent neural network for sentiment classification. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 1422–1432 (2015)CrossRef Tang, D., Qin, B., Liu, T.: Document modeling with gated recurrent neural network for sentiment classification. In: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, pp. 1422–1432 (2015)CrossRef
22.
Zurück zum Zitat Kuo, T.M., Lee, C.P., Lin, C.J.: Large-scale kernel ranksvm. In: Proceedings of the 2014 SIAM International Conference on Data Mining, pp. 812–820 (2014) Kuo, T.M., Lee, C.P., Lin, C.J.: Large-scale kernel ranksvm. In: Proceedings of the 2014 SIAM International Conference on Data Mining, pp. 812–820 (2014)
24.
Zurück zum Zitat Kendall, M.G.: A new measure of rank correlation. Biometrika. 30(1/2), 81–93 (1938)MATHCrossRef Kendall, M.G.: A new measure of rank correlation. Biometrika. 30(1/2), 81–93 (1938)MATHCrossRef
25.
Zurück zum Zitat Hamzah, F.B., Lau, C., Nazri, H., Ligot, D., Lee, G., Tan, C., Shaib, M., Zaidon, U., Abdullah, A., Chung, M., et al.: Coronatracker: worldwide COVID-19 outbreak data analysis and prediction. Bull. World Health Organ. 1(32) (2020) Hamzah, F.B., Lau, C., Nazri, H., Ligot, D., Lee, G., Tan, C., Shaib, M., Zaidon, U., Abdullah, A., Chung, M., et al.: Coronatracker: worldwide COVID-19 outbreak data analysis and prediction. Bull. World Health Organ. 1(32) (2020)
26.
Zurück zum Zitat Wu, J.T., Leung, K., Leung, G.M.: Nowcasting and forecasting the potential domestic and international spread of the 2019-ncov outbreak originating in Wuhan, China: a modelling study. Lancet. 395(10225), 689–697 (2020)CrossRef Wu, J.T., Leung, K., Leung, G.M.: Nowcasting and forecasting the potential domestic and international spread of the 2019-ncov outbreak originating in Wuhan, China: a modelling study. Lancet. 395(10225), 689–697 (2020)CrossRef
27.
Zurück zum Zitat Fumanelli, L., Ajelli, M., Manfredi, P., Vespignani, A., Merler, S.: Inferring the structure of social contacts from demographic data in the analysis of infectious diseases spread. PLoS Comput. Biol. 8(9), e1002673 (2012)MathSciNetCrossRef Fumanelli, L., Ajelli, M., Manfredi, P., Vespignani, A., Merler, S.: Inferring the structure of social contacts from demographic data in the analysis of infectious diseases spread. PLoS Comput. Biol. 8(9), e1002673 (2012)MathSciNetCrossRef
28.
Zurück zum Zitat Xia, S., Liu, J., Cheung, W.: Identifying the relative priorities of subpopulations for containing infectious disease spread. PLoS One. 8(6), e65271 (2013)CrossRef Xia, S., Liu, J., Cheung, W.: Identifying the relative priorities of subpopulations for containing infectious disease spread. PLoS One. 8(6), e65271 (2013)CrossRef
29.
Zurück zum Zitat Mossong, J., Hens, N., Jit, M., Beutels, P., Auranen, K., Mikolajczyk, R., Massari, M., Salmaso, S., Tomba, G.S., Wallinga, J., et al.: Social contacts and mixing patterns relevant to the spread of infectious diseases. PLoS Med. 5(3), e74 (2008)CrossRef Mossong, J., Hens, N., Jit, M., Beutels, P., Auranen, K., Mikolajczyk, R., Massari, M., Salmaso, S., Tomba, G.S., Wallinga, J., et al.: Social contacts and mixing patterns relevant to the spread of infectious diseases. PLoS Med. 5(3), e74 (2008)CrossRef
32.
Zurück zum Zitat Liu, T., Hu, J., Xiao, J., He, G., Kang, M., Rong, Z., Lin, L., Zhong, H., Huang, Q., Deng, A., et al.: Time-varying transmission dynamics of novel coronavirus pneumonia in china. BioRxiv. (2020) Liu, T., Hu, J., Xiao, J., He, G., Kang, M., Rong, Z., Lin, L., Zhong, H., Huang, Q., Deng, A., et al.: Time-varying transmission dynamics of novel coronavirus pneumonia in china. BioRxiv. (2020)
33.
Zurück zum Zitat Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., Ren, R., Leung, K.S., Lau, E.H., Wong, J.Y., et al.: Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N. Engl. J. Med. 382(13), 1199–1207 (2020)CrossRef Li, Q., Guan, X., Wu, P., Wang, X., Zhou, L., Tong, Y., Ren, R., Leung, K.S., Lau, E.H., Wong, J.Y., et al.: Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N. Engl. J. Med. 382(13), 1199–1207 (2020)CrossRef
34.
Zurück zum Zitat Epidemiology Working Group, et al.: Strategy and policy working group for NCIP epidemic response. Chinese Center for Disease Control and Prevention (2019) Epidemiology Working Group, et al.: Strategy and policy working group for NCIP epidemic response. Chinese Center for Disease Control and Prevention (2019)
35.
Zurück zum Zitat Hellewell, J., Abbott, S., Gimma, A., Bosse, N., Jarvis, C., Russell, T.W., Munday, J.D., Kucharski, A.J., Edmunds, W.J., Funk, S., et al.: Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. Lancet Glob. Heal. 8, e488–e496 (2020)CrossRef Hellewell, J., Abbott, S., Gimma, A., Bosse, N., Jarvis, C., Russell, T.W., Munday, J.D., Kucharski, A.J., Edmunds, W.J., Funk, S., et al.: Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. Lancet Glob. Heal. 8, e488–e496 (2020)CrossRef
36.
Zurück zum Zitat Sadique, M.Z., Adams, E.J., Edmunds, W.J.: Estimating the costs of school closure for mitigating an influenza pandemic. BMC Public Health. 8(1), 1–7 (2008)CrossRef Sadique, M.Z., Adams, E.J., Edmunds, W.J.: Estimating the costs of school closure for mitigating an influenza pandemic. BMC Public Health. 8(1), 1–7 (2008)CrossRef
37.
Zurück zum Zitat Hoang, T., Coletti, P., Melegaro, A., Wallinga, J., Grijalva, C.G., Edmunds, J.W., Beutels, P., Hens, N.: A systematic review of social contact surveys to inform transmission models of close-contact infections. Epidemiology (Cambridge, Mass.). 30(5), 723 (2019)CrossRef Hoang, T., Coletti, P., Melegaro, A., Wallinga, J., Grijalva, C.G., Edmunds, J.W., Beutels, P., Hens, N.: A systematic review of social contact surveys to inform transmission models of close-contact infections. Epidemiology (Cambridge, Mass.). 30(5), 723 (2019)CrossRef
Metadaten
Titel
Healthcare Applications
verfasst von
Yong Shi
Copyright-Jahr
2022
Verlag
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-16-3607-3_11