{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:25:21Z","timestamp":1750220721608,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":40,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,9,21]],"date-time":"2020-09-21T00:00:00Z","timestamp":1600646400000},"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":[[2020,9,21]]},"DOI":"10.1145\/3388440.3412463","type":"proceedings-article","created":{"date-parts":[[2020,11,10]],"date-time":"2020-11-10T12:43:43Z","timestamp":1605012223000},"page":"1-7","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Predicting Criticality in COVID-19 Patients"],"prefix":"10.1145","author":[{"given":"Roger A.","family":"Hallman","sequence":"first","affiliation":[{"name":"Thayer School of Engineering, Dartmouth College Hanover, New Hampshire, USA & Naval Information Warfare Center Pacific San Diego, California, USA and United States Department of Defense SMART Scholarship for Service Program"}]},{"given":"Anjali","family":"Chikkula","sequence":"additional","affiliation":[{"name":"Evercore Inc. Houston, Texas, USA and Dartmouth College, Hanover, New Hampshire, USA"}]},{"given":"Temiloluwa","family":"Prioleau","sequence":"additional","affiliation":[{"name":"Dartmouth College Hanover, New Hampshire, USA"}]}],"member":"320","published-online":{"date-parts":[[2020,11,10]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"rep","author":"Acr","year":"2020","unstructured":"Acr recommendations for the use of chest radiography and computed tomography (ct) for suspected covid-19 infection. Tech. rep ., American College of Radiology , March 22, 2020 . Acr recommendations for the use of chest radiography and computed tomography (ct) for suspected covid-19 infection. Tech. rep., American College of Radiology, March 22, 2020."},{"key":"e_1_3_2_1_2_1","volume-title":"https:\/\/coronavirus.jhu.edu\/","author":"Coronavirus","year":"2020","unstructured":"Coronavirus resource center. https:\/\/coronavirus.jhu.edu\/ , 2020 . Coronavirus resource center. https:\/\/coronavirus.jhu.edu\/, 2020."},{"key":"e_1_3_2_1_3_1","volume-title":"https:\/\/covidactnow.org\/","author":"Covid","year":"2020","unstructured":"Covid act now. https:\/\/covidactnow.org\/ , 2020 . Covid act now. https:\/\/covidactnow.org\/, 2020."},{"key":"e_1_3_2_1_4_1","volume-title":"Ai and data science supporting clinical decisions (from 28th mar to 3rd apr). https:\/\/www.kaggle.com\/einsteindata4u\/covid19#dataset.xlsx","author":"Diagnosis","year":"2020","unstructured":"Diagnosis of covid-19 and its clinical spectrum : Ai and data science supporting clinical decisions (from 28th mar to 3rd apr). https:\/\/www.kaggle.com\/einsteindata4u\/covid19#dataset.xlsx , 2020 . Diagnosis of covid-19 and its clinical spectrum: Ai and data science supporting clinical decisions (from 28th mar to 3rd apr). https:\/\/www.kaggle.com\/einsteindata4u\/covid19#dataset.xlsx, 2020."},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijid.2020.06.099"},{"key":"e_1_3_2_1_6_1","volume-title":"Statistical thinking for managerial decisions: Pooling the sampling estimates for mean, variance, and standard deviation","author":"Arsham H.","year":"2015","unstructured":"Arsham , H. Statistical thinking for managerial decisions: Pooling the sampling estimates for mean, variance, and standard deviation , 2015 . https:\/\/home.ubalt.edu\/ntsbarsh\/business-stat\/opre504.htm#rTwoIndTest. Arsham, H. Statistical thinking for managerial decisions: Pooling the sampling estimates for mean, variance, and standard deviation, 2015. https:\/\/home.ubalt.edu\/ntsbarsh\/business-stat\/opre504.htm#rTwoIndTest."},{"key":"e_1_3_2_1_7_1","volume-title":"Miraglia, J. L., Donato, T. H. R., and Chiavegatto Filho, A. D. P. Covid-19 diagnosis prediction in emergency care patients: a machine learning approach. medRxiv","author":"Batista A. F.","year":"2020","unstructured":"Batista , A. F. d. M ., Miraglia, J. L., Donato, T. H. R., and Chiavegatto Filho, A. D. P. Covid-19 diagnosis prediction in emergency care patients: a machine learning approach. medRxiv ( 2020 ). Batista, A. F. d. M., Miraglia, J. L., Donato, T. H. R., and Chiavegatto Filho, A. D. P. Covid-19 diagnosis prediction in emergency care patients: a machine learning approach. medRxiv (2020)."},{"key":"e_1_3_2_1_8_1","first-page":"1","article-title":"Arterial blood gases made easy. Clinical medicine (London","volume":"14","author":"Burns G. P","year":"2014","unstructured":"Burns , G. P . Arterial blood gases made easy. Clinical medicine (London , England) 14 , 1 ( 2014 ). Burns, G. P. Arterial blood gases made easy. Clinical medicine (London, England) 14, 1 (2014).","journal-title":"England)"},{"key":"e_1_3_2_1_9_1","volume-title":"Estimation of risk factors for covid-19 mortality - preliminary results. medRxiv","author":"Caramelo F.","year":"2020","unstructured":"Caramelo , F. , Ferreira , N. , and Oliveiros , B . Estimation of risk factors for covid-19 mortality - preliminary results. medRxiv ( 2020 ). Caramelo, F., Ferreira, N., and Oliveiros, B. Estimation of risk factors for covid-19 mortality - preliminary results. medRxiv (2020)."},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"e_1_3_2_1_11_1","volume-title":"https:\/\/github.com\/akchikkula111\/cs8920S\/tree\/gh-pages","author":"Chikkula A.","year":"2020","unstructured":"Chikkula , A. https:\/\/github.com\/akchikkula111\/cs8920S\/tree\/gh-pages , 2020 . Chikkula, A. https:\/\/github.com\/akchikkula111\/cs8920S\/tree\/gh-pages, 2020."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.7326\/M14-0698"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.2807\/1560-7917.ES.2020.25.3.2000045"},{"key":"e_1_3_2_1_14_1","volume-title":"Why am i, as a geriatric medicine fellow with symptoms, unable to get tested for covid-19 while politicians, oil executives, and nba players are? Journal of the American Geriatrics Society","author":"Dixon J.","year":"2020","unstructured":"Dixon , J. Why am i, as a geriatric medicine fellow with symptoms, unable to get tested for covid-19 while politicians, oil executives, and nba players are? Journal of the American Geriatrics Society ( 2020 ). Dixon, J. Why am i, as a geriatric medicine fellow with symptoms, unable to get tested for covid-19 while politicians, oil executives, and nba players are? Journal of the American Geriatrics Society (2020)."},{"key":"e_1_3_2_1_15_1","volume-title":"Health encyclopedia -- white blood cell count. Tech. rep","author":"Fetterman A.","year":"2020","unstructured":"Fetterman , A. , and Haldeman-Englert , C. Health encyclopedia -- white blood cell count. Tech. rep ., University of Rochester Medical Center , 2020 . Fetterman, A., and Haldeman-Englert, C. Health encyclopedia -- white blood cell count. Tech. rep., University of Rochester Medical Center, 2020."},{"key":"e_1_3_2_1_16_1","volume-title":"Health encyclopedia -- lactic acid dehydrogenase (blood). Tech. rep","author":"Fraser M.","year":"2020","unstructured":"Fraser , M. , and Haldeman-Englert , C. Health encyclopedia -- lactic acid dehydrogenase (blood). Tech. rep ., University of Rochester Medical Center , 2020 . Fraser, M., and Haldeman-Englert, C. Health encyclopedia -- lactic acid dehydrogenase (blood). Tech. rep., University of Rochester Medical Center, 2020."},{"key":"e_1_3_2_1_17_1","volume-title":"A tool to early predict severe 2019-novel coronavirus pneumonia (covid-19): A multicenter study using the risk nomogram in wuhan and guangdong, china. medRxiv","author":"Gong J.","year":"2020","unstructured":"Gong , J. , Ou , J. , Qiu , X. , Jie , Y. , Chen , Y. , Yuan , L. , Cao , J. , Tan , M. , Xu , W. , Zheng , F. , Shi , Y. , and Hu , B . A tool to early predict severe 2019-novel coronavirus pneumonia (covid-19): A multicenter study using the risk nomogram in wuhan and guangdong, china. medRxiv ( 2020 ). Gong, J., Ou, J., Qiu, X., Jie, Y., Chen, Y., Yuan, L., Cao, J., Tan, M., Xu, W., Zheng, F., Shi, Y., and Hu, B. A tool to early predict severe 2019-novel coronavirus pneumonia (covid-19): A multicenter study using the risk nomogram in wuhan and guangdong, china. medRxiv (2020)."},{"key":"e_1_3_2_1_18_1","volume-title":"Health encyclopedia -- c-reactive protein (blood). Tech. rep","author":"Greco F.","year":"2020","unstructured":"Greco , F. , and Sather , R . Health encyclopedia -- c-reactive protein (blood). Tech. rep ., University of Rochester Medical Center , 2020 . Greco, F., and Sather, R. Health encyclopedia -- c-reactive protein (blood). Tech. rep., University of Rochester Medical Center, 2020."},{"key":"e_1_3_2_1_19_1","volume-title":"National Institutes of Health","author":"Gulick R. M.","year":"2020","unstructured":"Gulick , R. M. , Lane , H. C. , Masur , H. , Pau , A. K. , Aberg , J. , Adimora , A. , Baker , J. , Bedimo , R. , Cantrill , S. , Collier , A. C. , Coopersmith , C. , Daar , E. , Davis , S. L. , Dzierba , A. L. , Evans , L. , Gandhi , R. , Glidden , D. , Grund , B. , Hardy , E. J. , Hughes , B. L. , Johnson , S. , Keller , M. J. , Kim , A. , Lennox , J. L. , Levy , M. M. , Martin , G. , Naggie , S. , Simpson , S. Q. , Swindells , S. , Tebas , P. , Tien , P. , Waghmare , A. A. , and Wilson , K. C . Coronavirus disease 2019 (covid-19) treatment guidelines. Tech. rep ., National Institutes of Health , 2020 . Gulick, R. M., Lane, H. C., Masur, H., Pau, A. K., Aberg, J., Adimora, A., Baker, J., Bedimo, R., Cantrill, S., Collier, A. C., Coopersmith, C., Daar, E., Davis, S. L., Dzierba, A. L., Evans, L., Gandhi, R., Glidden, D., Grund, B., Hardy, E. J., Hughes, B. L., Johnson, S., Keller, M. J., Kim, A., Lennox, J. L., Levy, M. M., Martin, G., Naggie, S., Simpson, S. Q., Swindells, S., Tebas, P., Tien, P., Waghmare, A. A., and Wilson, K. C. Coronavirus disease 2019 (covid-19) treatment guidelines. Tech. rep., National Institutes of Health, 2020."},{"key":"e_1_3_2_1_20_1","volume-title":"Health encyclopedia -- alt. Tech. rep","author":"Haldeman-Englert C.","year":"2020","unstructured":"Haldeman-Englert , C. , Trevino , H. , and Turley , K . Health encyclopedia -- alt. Tech. rep ., University of Rochester Medical Center , 2020 . Haldeman-Englert, C., Trevino, H., and Turley, K. Health encyclopedia -- alt. Tech. rep., University of Rochester Medical Center, 2020."},{"key":"e_1_3_2_1_21_1","volume-title":"First case of 2019 novel coronavirus in the united states. New England Journal of Medicine","author":"Holshue M. L.","year":"2020","unstructured":"Holshue , M. L. , DeBolt , C. , Lindqist , S. , Lofy , K. H. , Wiesman , J. , Bruce , H. , Spitters , C. , Ericson , K. , Wilkerson , S. , Tural , A. , First case of 2019 novel coronavirus in the united states. New England Journal of Medicine ( 2020 ). Holshue, M. L., DeBolt, C., Lindqist, S., Lofy, K. H., Wiesman, J., Bruce, H., Spitters, C., Ericson, K., Wilkerson, S., Tural, A., et al. First case of 2019 novel coronavirus in the united states. New England Journal of Medicine (2020)."},{"key":"e_1_3_2_1_22_1","volume-title":"Projecting the transmission dynamics of sars-cov-2 through the postpandemic period. Science","author":"Kissler S. M.","year":"2020","unstructured":"Kissler , S. M. , Tedijanto , C. , Goldstein , E. , Grad , Y. H. , and Lipsitch , M . Projecting the transmission dynamics of sars-cov-2 through the postpandemic period. Science ( 2020 ). Kissler, S. M., Tedijanto, C., Goldstein, E., Grad, Y. H., and Lipsitch, M. Projecting the transmission dynamics of sars-cov-2 through the postpandemic period. Science (2020)."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"crossref","unstructured":"Lu J. Hu S. Fan R. Liu Z. Yin X. Wang Q. Lv Q. Cai Z. Li H. Hu Y. etal Acp risk grade: a simple mortality index for patients with confirmed or suspected severe acute respiratory syndrome coronavirus 2 disease (covid-19) during the early stage of outbreak in wuhan china. Preprints with The Lancet (2020).  Lu J. Hu S. Fan R. Liu Z. Yin X. Wang Q. Lv Q. Cai Z. Li H. Hu Y. et al. Acp risk grade: a simple mortality index for patients with confirmed or suspected severe acute respiratory syndrome coronavirus 2 disease (covid-19) during the early stage of outbreak in wuhan china. Preprints with The Lancet (2020).","DOI":"10.1101\/2020.02.20.20025510"},{"key":"e_1_3_2_1_24_1","volume-title":"Optimally estimating the sample mean from the sample size, median, mid-range, and\/or mid-quartile range. Statistical methods in medical research 27, 6","author":"Luo D.","year":"2018","unstructured":"Luo , D. , Wan , X. , Liu , J. , and Tong , T . Optimally estimating the sample mean from the sample size, median, mid-range, and\/or mid-quartile range. Statistical methods in medical research 27, 6 ( 2018 ), 1785--1805. Luo, D., Wan, X., Liu, J., and Tong, T. Optimally estimating the sample mean from the sample size, median, mid-range, and\/or mid-quartile range. Statistical methods in medical research 27, 6 (2018), 1785--1805."},{"key":"e_1_3_2_1_25_1","volume-title":"Eastern Virginia Medical School","author":"Marik P. E.","year":"2020","unstructured":"Marik , P. E. Evms critical care covid-19 management protocol. Tech. rep ., Eastern Virginia Medical School , April 20, 2020 . Marik, P. E. Evms critical care covid-19 management protocol. Tech. rep., Eastern Virginia Medical School, April 20, 2020."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1440-1843.2006.00783.x"},{"key":"e_1_3_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13054-020-02930-6"},{"key":"e_1_3_2_1_28_1","volume-title":"Covid-19: The cidrap viewpoint. Tech. rep","author":"Moore K. A.","year":"2020","unstructured":"Moore , K. A. , Lipsitch , M. , Barry , J. M. , and Osterholm , M. T . Covid-19: The cidrap viewpoint. Tech. rep ., Center for Infectious Disease Research and Policy (CIDRAP) , University of Minnesota, April 30, 2020 . Moore, K. A., Lipsitch, M., Barry, J. M., and Osterholm, M. T. Covid-19: The cidrap viewpoint. Tech. rep., Center for Infectious Disease Research and Policy (CIDRAP), University of Minnesota, April 30, 2020."},{"key":"e_1_3_2_1_29_1","volume-title":"Persistence of antibodies against middle east respiratory syndrome coronavirus. Emerging infectious diseases 22, 10","author":"Payne D. C.","year":"2016","unstructured":"Payne , D. C. , Iblan , I. , Rha , B. , Alqasrawi , S. , Haddadin , A. , Al Nsour , M. , Alsanouri , T. , Ali , S. S. , Harcourt , J. , Miao , C. , Persistence of antibodies against middle east respiratory syndrome coronavirus. Emerging infectious diseases 22, 10 ( 2016 ), 1824. Payne, D. C., Iblan, I., Rha, B., Alqasrawi, S., Haddadin, A., Al Nsour, M., Alsanouri, T., Ali, S. S., Harcourt, J., Miao, C., et al. Persistence of antibodies against middle east respiratory syndrome coronavirus. Emerging infectious diseases 22, 10 (2016), 1824."},{"key":"e_1_3_2_1_30_1","unstructured":"Petrilli C. M. Jones S. A. Yang J. R0ajagopalan H. O'Donnell L. F. Chernyak Y. Tobin K. Cerfolio R. J. Francois F. and Horwitz L. I. Factors associated with hospitalization and critical illness among 4 103 patients with covid-19 disease in new york city.  Petrilli C. M. Jones S. A. Yang J. R0ajagopalan H. O'Donnell L. F. Chernyak Y. Tobin K. Cerfolio R. J. Francois F. and Horwitz L. I. Factors associated with hospitalization and critical illness among 4 103 patients with covid-19 disease in new york city."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13054-020-2833-7"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcv.2020.104357"},{"key":"e_1_3_2_1_33_1","volume-title":"April 8","author":"Strickler L.","year":"2020","unstructured":"Strickler , L. , and Kaplan , A . Private labs do 85 percent of u.s. covid-19 tests but still struggle with backlogs, shortages. https:\/\/www.nbcnews.com\/health\/health-news\/private-labs-do-85-percent-u-s-covid-19-tests-n1177866 , April 8 , 2020 . Strickler, L., and Kaplan, A. Private labs do 85 percent of u.s. covid-19 tests but still struggle with backlogs, shortages. https:\/\/www.nbcnews.com\/health\/health-news\/private-labs-do-85-percent-u-s-covid-19-tests-n1177866, April 8, 2020."},{"key":"e_1_3_2_1_34_1","volume-title":"Estimating the sample mean and standard deviation from the sample size, median, range and\/or interquartile range. BMC medical research methodology 14, 1","author":"Wan X.","year":"2014","unstructured":"Wan , X. , Wang , W. , Liu , J. , and Tong , T . Estimating the sample mean and standard deviation from the sample size, median, range and\/or interquartile range. BMC medical research methodology 14, 1 ( 2014 ), 135. Wan, X., Wang, W., Liu, J., and Tong, T. Estimating the sample mean and standard deviation from the sample size, median, range and\/or interquartile range. BMC medical research methodology 14, 1 (2014), 135."},{"key":"e_1_3_2_1_35_1","first-page":"369","article-title":"Prediction models for diagnosis and prognosis of covid-19 infection: systematic review and critical appraisal","author":"Wynants L.","year":"2020","unstructured":"Wynants , L. , Van Calster , B. , Bonten , M. M. J. , Collins , G. S. , Debray , T. P. A. , De Vos , M. , Haller , M. C. , Heinze , G. , Moons , K. G. M. , Riley , R. D. , Schuit , E. , Smits , L. J. M. , Snell , K. I. E. , Steyerberg , E. W. , Wallisch , C. , and van Smeden , M . Prediction models for diagnosis and prognosis of covid-19 infection: systematic review and critical appraisal . BMJ 369 ( 2020 ). Wynants, L., Van Calster, B., Bonten, M. M. J., Collins, G. S., Debray, T. P. A., De Vos, M., Haller, M. C., Heinze, G., Moons, K. G. M., Riley, R. D., Schuit, E., Smits, L. J. M., Snell, K. I. E., Steyerberg, E. W., Wallisch, C., and van Smeden, M. Prediction models for diagnosis and prognosis of covid-19 infection: systematic review and critical appraisal. BMJ 369 (2020).","journal-title":"BMJ"},{"key":"e_1_3_2_1_36_1","volume-title":"Development and external validation of a prognostic multivariable model on admission for hospitalized patients with covid-19. Preprints with The Lancet","author":"Xie J.","year":"2020","unstructured":"Xie , J. , Hungerford , D. , Chen , H. , Abrams , S. T. , Li , S. , Wang , G. , Wang , Y. , Kang , H. , Bonnett , L. , Zheng , R. , Development and external validation of a prognostic multivariable model on admission for hospitalized patients with covid-19. Preprints with The Lancet ( 2020 ). Xie, J., Hungerford, D., Chen, H., Abrams, S. T., Li, S., Wang, G., Wang, Y., Kang, H., Bonnett, L., Zheng, R., et al. Development and external validation of a prognostic multivariable model on admission for hospitalized patients with covid-19. Preprints with The Lancet (2020)."},{"key":"e_1_3_2_1_37_1","volume-title":"A machine learning-based model for survival prediction in patients with severe covid-19 infection. medRxiv","author":"Yan L.","year":"2020","unstructured":"Yan , L. , Zhang , H.-T. , Goncalves , J. , Xiao , Y. , Wang , M. , Guo , Y. , Sun , C. , Tang , X. , Jin , L. , Zhang , M. , Huang , X. , Xiao , Y. , Cao , H. , Chen , Y. , Ren , T. , Wang , F. , Xiao , Y. , Huang , S. , Tan , X. , Huang , N. , Jiao , B. , Zhang , Y. , Luo , A. , Mombaerts , L. , Jin , J. , Cao , Z. , Li , S. , Xu , H. , and Yuan , Y . A machine learning-based model for survival prediction in patients with severe covid-19 infection. medRxiv ( 2020 ). Yan, L., Zhang, H.-T., Goncalves, J., Xiao, Y., Wang, M., Guo, Y., Sun, C., Tang, X., Jin, L., Zhang, M., Huang, X., Xiao, Y., Cao, H., Chen, Y., Ren, T., Wang, F., Xiao, Y., Huang, S., Tan, X., Huang, N., Jiao, B., Zhang, Y., Luo, A., Mombaerts, L., Jin, J., Cao, Z., Li, S., Xu, H., and Yuan, Y. A machine learning-based model for survival prediction in patients with severe covid-19 infection. medRxiv (2020)."},{"key":"e_1_3_2_1_38_1","volume-title":"Prediction of criticality in patients with severe covid-19 infection using three clinical features: a machine learning-based prognostic model with clinical data in wuhan. medRxiv","author":"Yan L.","year":"2020","unstructured":"Yan , L. , Zhang , H.-T. , Xiao , Y. , Wang , M. , Sun , C. , Liang , J. , Li , S. , Zhang , M. , Guo , Y. , Xiao , Y. , Tang , X. , Cao , H. , Tan , X. , Huang , N. , Jiao , B. , Luo , A. , Cao , Z. , Xu , H. , and Yuan , Y . Prediction of criticality in patients with severe covid-19 infection using three clinical features: a machine learning-based prognostic model with clinical data in wuhan. medRxiv ( 2020 ). Yan, L., Zhang, H.-T., Xiao, Y., Wang, M., Sun, C., Liang, J., Li, S., Zhang, M., Guo, Y., Xiao, Y., Tang, X., Cao, H., Tan, X., Huang, N., Jiao, B., Luo, A., Cao, Z., Xu, H., and Yuan, Y. Prediction of criticality in patients with severe covid-19 infection using three clinical features: a machine learning-based prognostic model with clinical data in wuhan. medRxiv (2020)."},{"key":"e_1_3_2_1_39_1","volume-title":"Epidemiological and clinical features of covid-19 patients with and without pneumonia in beijing, china. Medrxiv","author":"Yang P.","year":"2020","unstructured":"Yang , P. , Ding , Y. , Xu , Z. , Pu , R. , Li , P. , Yan , J. , Liu , J. , Meng , F. , Huang , L. , Shi , L. , Epidemiological and clinical features of covid-19 patients with and without pneumonia in beijing, china. Medrxiv ( 2020 ). Yang, P., Ding, Y., Xu, Z., Pu, R., Li, P., Yan, J., Liu, J., Meng, F., Huang, L., Shi, L., et al. Epidemiological and clinical features of covid-19 patients with and without pneumonia in beijing, china. Medrxiv (2020)."},{"key":"e_1_3_2_1_40_1","volume-title":"-H. Chest radiographic and ct findings of the 2019 novel coronavirus disease (covid-19): analysis of nine patients treated in korea. Korean journal of radiology 21, 4","author":"Yoon S. H.","year":"2020","unstructured":"Yoon , S. H. , Lee , K. H. , Kim , J. Y. , Lee , Y. K. , Ko , H. , Kim , K. H. , Park , C. M. , and Kim , Y . -H. Chest radiographic and ct findings of the 2019 novel coronavirus disease (covid-19): analysis of nine patients treated in korea. Korean journal of radiology 21, 4 ( 2020 ), 494--500. Yoon, S. H., Lee, K. H., Kim, J. Y., Lee, Y. K., Ko, H., Kim, K. H., Park, C. M., and Kim, Y.-H. Chest radiographic and ct findings of the 2019 novel coronavirus disease (covid-19): analysis of nine patients treated in korea. Korean journal of radiology 21, 4 (2020), 494--500."}],"event":{"name":"BCB '20: 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics","sponsor":["SIGBio ACM Special Interest Group on Bioinformatics"],"location":"Virtual Event USA","acronym":"BCB '20"},"container-title":["Proceedings of the 11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3388440.3412463","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3388440.3412463","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:33:30Z","timestamp":1750199610000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3388440.3412463"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,21]]},"references-count":40,"alternative-id":["10.1145\/3388440.3412463","10.1145\/3388440"],"URL":"https:\/\/doi.org\/10.1145\/3388440.3412463","relation":{},"subject":[],"published":{"date-parts":[[2020,9,21]]},"assertion":[{"value":"2020-11-10","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}