{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,3]],"date-time":"2025-08-03T23:08:33Z","timestamp":1754262513546,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":43,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,8,14]],"date-time":"2020-08-14T00:00:00Z","timestamp":1597363200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,8,14]]},"DOI":"10.1145\/3418094.3418134","type":"proceedings-article","created":{"date-parts":[[2020,10,15]],"date-time":"2020-10-15T18:29:38Z","timestamp":1602786578000},"page":"37-44","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Disease Predictive Modeling for Healthcare Management System"],"prefix":"10.1145","author":[{"given":"Khulood","family":"Nakhat","sequence":"first","affiliation":[{"name":"Department of Computer and Software Engineering, College of E&ME, NUST, Islamabad, Pakistan"}]},{"given":"Fatima","family":"Khalique","sequence":"additional","affiliation":[{"name":"Department of Computer and Software Engineering, College of E&ME, NUST, Islamabad, Pakistan"}]},{"given":"Shoab Ahmed","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Computer and Software Engineering, College of E&ME, NUST, Islamabad, Pakistan"}]}],"member":"320","published-online":{"date-parts":[[2020,10,15]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"I.: A Framework for Public Health Monitoring, Analytics and Research","author":"Khalique F.","year":"2019","unstructured":"Khalique , F. , Khan , S.A. , Nosheen , I.: A Framework for Public Health Monitoring, Analytics and Research . IEEE Access 7, 101309--101326 ( 2019 ). Khalique, F., Khan, S.A., Nosheen, I.: A Framework for Public Health Monitoring, Analytics and Research. IEEE Access 7, 101309--101326 (2019)."},{"key":"e_1_3_2_1_2_1","first-page":"404","volume-title":"Science and Information Conference","author":"Khalique F.","year":"2018","unstructured":"Khalique , F. , Khan , S.A. , Safdar , H. : Decision tree-based anonymized electronic health record fusion for public health informatics . In: Science and Information Conference 2018 , pp. 404 -- 414 . Springer Khalique, F., Khan, S.A., Safdar, H.: Decision tree-based anonymized electronic health record fusion for public health informatics. In: Science and Information Conference 2018, pp. 404--414. Springer"},{"key":"e_1_3_2_1_3_1","volume-title":"Song","author":"Liu K.","year":"2020","unstructured":"Liu , K. , Hou , X. , Ren , Z. , Lowe , R. , Wang , Y. , Li , R. , Liu , X. , Sun , J. , Lu , L. , Song , X. : Climate factors and the East Asian summer monsoon may drive large outbreaks of dengue in China. Environmental Research , 109190 ( 2020 ). Liu, K., Hou, X., Ren, Z., Lowe, R., Wang, Y., Li, R., Liu, X., Sun, J., Lu, L., Song, X.: Climate factors and the East Asian summer monsoon may drive large outbreaks of dengue in China. Environmental Research, 109190 (2020)."},{"key":"e_1_3_2_1_4_1","volume-title":": World malaria report","author":"Organization","year":"2019","unstructured":"Organization , W.H. : World malaria report 2019 . In . (2019) Organization, W.H.: World malaria report 2019. In. (2019)"},{"key":"e_1_3_2_1_5_1","volume-title":"S11-S15","author":"McEwen B.S.","year":"2008","unstructured":"McEwen , B.S. : Understanding the potency of stressful early life experiences on brain and body function. Metabolism 57 , S11-S15 ( 2008 ). McEwen, B.S.: Understanding the potency of stressful early life experiences on brain and body function. Metabolism 57, S11-S15 (2008)."},{"key":"e_1_3_2_1_6_1","volume-title":"French","author":"Oakley N.J.","year":"2020","unstructured":"Oakley , N.J. , Kneale , D. , Mann , M. , Hilliar , M. , Dayan , C. , Gregory , J.W. , French , R. : Type 1 diabetes mellitus and educational attainment in childhood: a systematic review. BMJ open 10(1) ( 2020 ). Oakley, N.J., Kneale, D., Mann, M., Hilliar, M., Dayan, C., Gregory, J.W., French, R.: Type 1 diabetes mellitus and educational attainment in childhood: a systematic review. BMJ open 10(1) (2020)."},{"key":"e_1_3_2_1_7_1","volume-title":"A prediction model for the risk of incident chronic kidney disease. The American journal of medicine, 123(9), 836--846","author":"Chien K. L.","year":"2010","unstructured":"Chien , K. L. , Lin , H. J. , Lee , B. C. , Hsu , H. C. , Lee , Y. T. , & Chen , M. F. ( 2010 ). A prediction model for the risk of incident chronic kidney disease. The American journal of medicine, 123(9), 836--846 . Chien, K. L., Lin, H. J., Lee, B. C., Hsu, H. C., Lee, Y. T., & Chen, M. F. (2010). A prediction model for the risk of incident chronic kidney disease. The American journal of medicine, 123(9), 836--846."},{"key":"e_1_3_2_1_8_1","volume-title":"Application of a system dynamics model in forecasting the supply and age distribution of physicians. Croatian Medical Journal, 61(2)","author":"Reli\u0107 D.","year":"2020","unstructured":"Reli\u0107 , D. , & Bo\u017eikov , J. ( 2020 ). Application of a system dynamics model in forecasting the supply and age distribution of physicians. Croatian Medical Journal, 61(2) . Reli\u0107, D., & Bo\u017eikov, J. (2020). Application of a system dynamics model in forecasting the supply and age distribution of physicians. Croatian Medical Journal, 61(2)."},{"key":"e_1_3_2_1_9_1","volume-title":"Forecasting the medical workforce: a stochastic agent-based simulation approach. Health care management science, 21(1), 52--75","author":"Lopes M. A.","year":"2018","unstructured":"Lopes , M. A. , Almeida , \u00c1. S. , & Almada-Lobo , B. ( 2018 ). Forecasting the medical workforce: a stochastic agent-based simulation approach. Health care management science, 21(1), 52--75 Lopes, M. A., Almeida, \u00c1. S., & Almada-Lobo, B. (2018). Forecasting the medical workforce: a stochastic agent-based simulation approach. Health care management science, 21(1), 52--75"},{"key":"e_1_3_2_1_10_1","volume-title":"S1.","author":"Zhao J.","year":"2015","unstructured":"Zhao , J. , Henriksson , A. , Asker , L. , & Bostr\u00f6m , H. ( 2015 ). Predictive modeling of structured electronic health records for adverse drug event detection. BMC medical informatics and decision making, 15(S4) , S1. Zhao, J., Henriksson, A., Asker, L., & Bostr\u00f6m, H. (2015). Predictive modeling of structured electronic health records for adverse drug event detection. BMC medical informatics and decision making, 15(S4), S1."},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2015.04.066"},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2019.05.008"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1080\/10920277.2015.1110491"},{"key":"e_1_3_2_1_14_1","volume-title":"Forecasting Blood Donor Response Using Predictive Modelling Approach","author":"Marade C.","year":"2019","unstructured":"Marade , C. , Pradeep , A. , Mohanty , D. , & Patil , C. ( 2019 ). Forecasting Blood Donor Response Using Predictive Modelling Approach . Marade, C., Pradeep, A., Mohanty, D., & Patil, C. (2019). Forecasting Blood Donor Response Using Predictive Modelling Approach."},{"key":"e_1_3_2_1_15_1","volume-title":"Characterising and predicting persistent high-cost utilisers in healthcare: a retrospective cohort study in Singapore. BMJ open, 10(1)","author":"Ng S. H. X.","year":"2020","unstructured":"Ng , S. H. X. , Rahman , N. , Ang , I. Y. H. , Sridharan , S. , Ramachandran , S. , Wang , D. D., . .. & Tan , X. Q. ( 2020 ). Characterising and predicting persistent high-cost utilisers in healthcare: a retrospective cohort study in Singapore. BMJ open, 10(1) . Ng, S. H. X., Rahman, N., Ang, I. Y. H., Sridharan, S., Ramachandran, S., Wang, D. D., ... & Tan, X. Q. (2020). Characterising and predicting persistent high-cost utilisers in healthcare: a retrospective cohort study in Singapore. BMJ open, 10(1)."},{"key":"e_1_3_2_1_16_1","volume-title":"Who is not coming to clinic? A predictive model of excessive missed appointments in persons with multiple sclerosis. Multiple sclerosis and related disorders, 38, 101513","author":"Gromisch E. S.","year":"2020","unstructured":"Gromisch , E. S. , Turner , A. P. , Leipertz , S. L. , Beauvais , J. , & Haselkorn , J. K. ( 2020 ). Who is not coming to clinic? A predictive model of excessive missed appointments in persons with multiple sclerosis. Multiple sclerosis and related disorders, 38, 101513 . Gromisch, E. S., Turner, A. P., Leipertz, S. L., Beauvais, J., & Haselkorn, J. K. (2020). Who is not coming to clinic? A predictive model of excessive missed appointments in persons with multiple sclerosis. Multiple sclerosis and related disorders, 38, 101513."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.3390\/ijerph17113763"},{"issue":"4","key":"e_1_3_2_1_18_1","first-page":"333","article-title":"Applying linear regression statistical method to predict the epidemic of hemorrhagic fever with renal syndrome","volume":"17","author":"Wang Y. J.","year":"2006","unstructured":"Wang , Y. J. , Zhao , T. Q. , Wang , P. , Li , S. Q. , Huang , Z. , Yang , G. Q., . .. & Liu , B. ( 2006 ). Applying linear regression statistical method to predict the epidemic of hemorrhagic fever with renal syndrome . Chinese Journal of Vector Biology and Control , 17 ( 4 ), 333 -- 334 . Wang, Y. J., Zhao, T. Q., Wang, P., Li, S. Q., Huang, Z., Yang, G. Q., ... & Liu, B. (2006). Applying linear regression statistical method to predict the epidemic of hemorrhagic fever with renal syndrome. Chinese Journal of Vector Biology and Control, 17(4), 333--4.","journal-title":"Chinese Journal of Vector Biology and Control"},{"key":"e_1_3_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1186\/1476-072X-8-1"},{"issue":"6","key":"e_1_3_2_1_20_1","first-page":"839","article-title":"Appling grey swing model to predict the incidence trend of hemorrhagic fever with renal syndrome in Shenyang","volume":"37","author":"Guo L. C.","year":"2008","unstructured":"Guo , L. C. , Wu , W. , Guo , J. Q. , Wang , P. , & Zhou , B. S. ( 2008 ). Appling grey swing model to predict the incidence trend of hemorrhagic fever with renal syndrome in Shenyang . Journal of China Medical University , 37 ( 6 ), 839 -- 842 . Guo, L. C., Wu, W., Guo, J. Q., Wang, P., & Zhou, B. S. (2008). Appling grey swing model to predict the incidence trend of hemorrhagic fever with renal syndrome in Shenyang. Journal of China Medical University, 37(6), 839--842.","journal-title":"Journal of China Medical University"},{"issue":"3","key":"e_1_3_2_1_21_1","first-page":"223","article-title":"Prediction for incidence of hemorrhagic fever with renal syndrome with back propagation artificial neural network model","volume":"17","author":"Wu Z.","year":"2006","unstructured":"Wu , Z. , Wu , W. , & Wang , P. ( 2006 ). Prediction for incidence of hemorrhagic fever with renal syndrome with back propagation artificial neural network model . Chinese Journal of Vector Biology and Control , 17 ( 3 ), 223 . Wu, Z., Wu, W., & Wang, P. (2006). Prediction for incidence of hemorrhagic fever with renal syndrome with back propagation artificial neural network model. Chinese Journal of Vector Biology and Control, 17(3), 223.","journal-title":"Chinese Journal of Vector Biology and Control"},{"key":"e_1_3_2_1_22_1","volume-title":"International Journal of Computers and Applications, 1--6","author":"Tseng Y.-J.","year":"2019","unstructured":"Tseng , Y.-J. , Shih , Y.-L. : Developing epidemic forecasting models to assist disease surveillance for influenza with electronic health records . International Journal of Computers and Applications, 1--6 ( 2019 ). Tseng, Y.-J., Shih, Y.-L.: Developing epidemic forecasting models to assist disease surveillance for influenza with electronic health records. International Journal of Computers and Applications, 1--6 (2019)."},{"key":"e_1_3_2_1_23_1","volume-title":"Jiang","author":"Wang Y.-w.","year":"2018","unstructured":"Wang , Y.-w. , Shen , Z.-z. , Jiang , Y. : Comparison of ARIMA and GM (1, 1) models for prediction of hepatitis B in China. PloS one 13(9) ( 2018 ). Wang, Y.-w., Shen, Z.-z., Jiang, Y.: Comparison of ARIMA and GM (1, 1) models for prediction of hepatitis B in China. PloS one 13(9) (2018)."},{"key":"e_1_3_2_1_24_1","volume-title":"China. PloS one 11(6)","author":"Wei W.","year":"2016","unstructured":"Wei , W. , Jiang , J. , Liang , H. , Gao , L. , Liang , B. , Huang , J. , Zang , N. , Liao , Y. , Yu , J. , Lai , J. : (Reference8)Application of a combined model with autoregressive integrated moving average (ARIMA) and generalized regression neural network (GRNN) in forecasting hepatitis incidence in Heng County , China. PloS one 11(6) ( 2016 ). Wei, W., Jiang, J., Liang, H., Gao, L., Liang, B., Huang, J., Zang, N., Liao, Y., Yu, J., Lai, J.: (Reference8)Application of a combined model with autoregressive integrated moving average (ARIMA) and generalized regression neural network (GRNN) in forecasting hepatitis incidence in Heng County, China. PloS one 11(6) (2016)."},{"key":"e_1_3_2_1_25_1","volume-title":"Hasan","author":"Rahman A.","year":"2017","unstructured":"Rahman , A. , Hasan , M.M. : Modeling and forecasting of carbon dioxide emissions in Bangladesh using Autoregressive Integrated Moving Average (ARIMA) models. Open Journal of Statistics 7(4), 560--566 ( 2017 ). Rahman, A., Hasan, M.M.: Modeling and forecasting of carbon dioxide emissions in Bangladesh using Autoregressive Integrated Moving Average (ARIMA) models. Open Journal of Statistics 7(4), 560--566 (2017)."},{"key":"e_1_3_2_1_26_1","volume-title":"Jelinski","author":"Coward S.","year":"2019","unstructured":"Coward , S. , Clement , F. , Benchimol , E.I. , Bernstein , C.N. , Avina-Zubieta , J.A. , Bitton , A. , Carroll , M.W. , Hazlewood , G. , Jacobson , K. , Jelinski , S. : Past and future burden of inflammatory bowel diseases based on modeling of population-based data. Gastroenterology 156(5), 1345--1353. e1344 ( 2019 ). Coward, S., Clement, F., Benchimol, E.I., Bernstein, C.N., Avina-Zubieta, J.A., Bitton, A., Carroll, M.W., Hazlewood, G., Jacobson, K., Jelinski, S.: Past and future burden of inflammatory bowel diseases based on modeling of population-based data. Gastroenterology 156(5), 1345--1353. e1344 (2019)."},{"key":"e_1_3_2_1_27_1","volume-title":"Machin","author":"Earnest A.","year":"2012","unstructured":"Earnest , A. , Tan , S.B. , Wilder-Smith , A. , Machin , D. : Comparing statistical models to predict dengue fever notifications. Computational and mathematical methods in medicine 2012 (2012). Earnest, A., Tan, S.B., Wilder-Smith, A., Machin, D.: Comparing statistical models to predict dengue fever notifications. Computational and mathematical methods in medicine 2012 (2012)."},{"key":"e_1_3_2_1_28_1","volume-title":"Zhai","author":"Wang T.","year":"2004","unstructured":"Wang , T. , Zhou , Y. , Wang , L. , Huang , Z. , Cui , F. , Zhai , S. : Using autoregressive integrated moving average model to predict the incidence of hemorrhagic fever with renal syndrome in Zibo, China, 2004 --2014. Japanese journal of infectious diseases, JJID. 2014.2567 (2015). Wang, T., Zhou, Y., Wang, L., Huang, Z., Cui, F., Zhai, S.: Using autoregressive integrated moving average model to predict the incidence of hemorrhagic fever with renal syndrome in Zibo, China, 2004--2014. Japanese journal of infectious diseases, JJID. 2014.2567 (2015)."},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCEREC.2015.7337047"},{"key":"e_1_3_2_1_30_1","volume-title":"Rozi","author":"Akhtar S.","year":"2009","unstructured":"Akhtar , S. , Rozi , S. : An autoregressive integrated moving average model for short-term prediction of hepatitis C virus seropositivity among male volunteer blood donors in Karachi, Pakistan. World Journal of Gastroenterology: WJG 15(13), 1607 ( 2009 ). Akhtar, S., Rozi, S.: An autoregressive integrated moving average model for short-term prediction of hepatitis C virus seropositivity among male volunteer blood donors in Karachi, Pakistan. World Journal of Gastroenterology: WJG 15(13), 1607 (2009)."},{"key":"e_1_3_2_1_31_1","volume-title":"Roy","author":"Trottier H.","year":"2006","unstructured":"Trottier , H. , Philippe , P. , Roy , R. : Stochastic modeling of empirical time series of childhood infectious diseases data before and after mass vaccination. Emerging themes in epidemiology 3(1), 9 ( 2006 ). Trottier, H., Philippe, P., Roy, R.: Stochastic modeling of empirical time series of childhood infectious diseases data before and after mass vaccination. Emerging themes in epidemiology 3(1), 9 (2006)."},{"key":"e_1_3_2_1_32_1","volume-title":"Ciccozzi","author":"Benvenuto D.","year":"2019","unstructured":"Benvenuto , D. , Giovanetti , M. , Vassallo , L. , Angeletti , S. , Ciccozzi , M. : Application of the ARIMA model on the COVID- 2019 epidemic dataset. Data in brief, 105340 (2020). Benvenuto, D., Giovanetti, M., Vassallo, L., Angeletti, S., Ciccozzi, M.: Application of the ARIMA model on the COVID-2019 epidemic dataset. Data in brief, 105340 (2020)."},{"key":"e_1_3_2_1_33_1","volume-title":"Ismail","author":"Al Wadia M.","year":"2011","unstructured":"Al Wadia , M. , Ismail , M.T. : Selecting wavelet transforms model in forecasting financial time series data based on ARIMA model. Applied Mathematical Sciences 5(7), 315--326 ( 2011 ). Al Wadia, M., Ismail, M.T.: Selecting wavelet transforms model in forecasting financial time series data based on ARIMA model. Applied Mathematical Sciences 5(7), 315--326 (2011)."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.5901\/ajis.2014.v3n4p429"},{"key":"e_1_3_2_1_35_1","volume-title":"Abaye","author":"Adedia D.","year":"2018","unstructured":"Adedia , D. , Nanga , S. , Appiah , S.K. , Lotsi , A. , Abaye , D.A. : Box-Jenkins' Methodology in Predicting Maternal Mortality Records from a Public Health Facility in Ghana. Open Journal of Applied Sciences 8(06), 189 ( 2018 ). Adedia, D., Nanga, S., Appiah, S.K., Lotsi, A., Abaye, D.A.: Box-Jenkins' Methodology in Predicting Maternal Mortality Records from a Public Health Facility in Ghana. Open Journal of Applied Sciences 8(06), 189 (2018)."},{"key":"e_1_3_2_1_36_1","volume-title":"Bonga","author":"Nyoni T.","year":"2019","unstructured":"Nyoni , T. , Bonga , W.G. : Predicting Net Foreign Direct Investment in Nigeria using Box-Jenkins ARIMA Approach. DRJ-Journal of Economics & Finance 4(2), 30--37 ( 2019 ). Nyoni, T., Bonga, W.G.: Predicting Net Foreign Direct Investment in Nigeria using Box-Jenkins ARIMA Approach. DRJ-Journal of Economics & Finance 4(2), 30--37 (2019)."},{"key":"e_1_3_2_1_37_1","volume-title":"Koehler","author":"Hyndman R.J.","year":"2006","unstructured":"Hyndman , R.J. , Koehler , A.B. : Another look at measures of forecast accuracy. International journal of forecasting 22(4), 679--688 ( 2006 ). Hyndman, R.J., Koehler, A.B.: Another look at measures of forecast accuracy. International journal of forecasting 22(4), 679--688 (2006)."},{"key":"e_1_3_2_1_38_1","volume-title":"Musgrove","author":"Jamison D.T.","year":"2006","unstructured":"Jamison , D.T. , Breman , J.G. , Measham , A.R. , Alleyne , G. , Claeson , M. , Evans , D.B. , Jha , P. , Mills , A. , Musgrove , P. : Disease control priorities in developing countries. The World Bank , ( 2006 ) Jamison, D.T., Breman, J.G., Measham, A.R., Alleyne, G., Claeson, M., Evans, D.B., Jha, P., Mills, A., Musgrove, P.: Disease control priorities in developing countries. The World Bank, (2006)"},{"key":"e_1_3_2_1_39_1","volume-title":"Yang","author":"Liu Q.","year":"2011","unstructured":"Liu , Q. , Liu , X. , Jiang , B. , Yang , W. : Forecasting incidence of hemorrhagic fever with renal syndrome in China using ARIMA model. BMC infectious diseases 11(1), 218 ( 2011 ). Liu, Q., Liu, X., Jiang, B., Yang, W.: Forecasting incidence of hemorrhagic fever with renal syndrome in China using ARIMA model. BMC infectious diseases 11(1), 218 (2011)."},{"key":"e_1_3_2_1_40_1","volume-title":"Sin","author":"Earnest A.","year":"2005","unstructured":"Earnest , A. , Chen , M.I. , Ng , D. , Sin , L.Y. : Using autoregressive integrated moving average (ARIMA) models to predict and monitor the number of beds occupied during a SARS outbreak in a tertiary hospital in Singapore. BMC Health Services Research 5(1), 36 ( 2005 ). Earnest, A., Chen, M.I., Ng, D., Sin, L.Y.: Using autoregressive integrated moving average (ARIMA) models to predict and monitor the number of beds occupied during a SARS outbreak in a tertiary hospital in Singapore. BMC Health Services Research 5(1), 36 (2005)."},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"crossref","unstructured":"Garc\u00eda-D\u00edaz J.C.: Monitoring and forecasting nitrate concentration in the groundwater using statistical process control and time series analysis: a case study. Stochastic Environmental Research and Risk Assessment 25(3) 331--339 (2011).  Garc\u00eda-D\u00edaz J.C.: Monitoring and forecasting nitrate concentration in the groundwater using statistical process control and time series analysis: a case study. Stochastic Environmental Research and Risk Assessment 25(3) 331--339 (2011).","DOI":"10.1007\/s00477-010-0371-6"},{"key":"e_1_3_2_1_42_1","volume-title":"Rawnsley","author":"McGee V.E.","year":"1979","unstructured":"McGee , V.E. , Jenkins , E. , Rawnsley , H.M. : Statistical forecasting in a hospital clinical laboratory. Journal of medical systems 3(3-4), 161--174 ( 1979 ). McGee, V.E., Jenkins, E., Rawnsley, H.M.: Statistical forecasting in a hospital clinical laboratory. Journal of medical systems 3(3-4), 161--174 (1979)."},{"key":"e_1_3_2_1_43_1","volume-title":"Big data's role in precision public health. Frontiers in public health 6, 68","author":"Dolley S.","year":"2018","unstructured":"Dolley , S. : Big data's role in precision public health. Frontiers in public health 6, 68 ( 2018 ). Dolley, S.: Big data's role in precision public health. Frontiers in public health 6, 68 (2018)."}],"event":{"name":"ICMHI 2020: 2020 4th International Conference on Medical and Health Informatics","sponsor":["University of Tsukuba University of Tsukuba"],"location":"Kamakura City Japan","acronym":"ICMHI 2020"},"container-title":["Proceedings of the 4th International Conference on Medical and Health Informatics"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3418094.3418134","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3418094.3418134","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T21:31:36Z","timestamp":1750195896000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3418094.3418134"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,14]]},"references-count":43,"alternative-id":["10.1145\/3418094.3418134","10.1145\/3418094"],"URL":"https:\/\/doi.org\/10.1145\/3418094.3418134","relation":{},"subject":[],"published":{"date-parts":[[2020,8,14]]},"assertion":[{"value":"2020-10-15","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}