{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,5]],"date-time":"2026-05-05T14:42:36Z","timestamp":1777992156668,"version":"3.51.4"},"publisher-location":"New York, NY, USA","reference-count":120,"publisher":"ACM","license":[{"start":{"date-parts":[[2024,5,11]],"date-time":"2024-05-11T00:00:00Z","timestamp":1715385600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/https:\/\/doi.org\/10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["DK125718"],"award-info":[{"award-number":["DK125718"]}],"id":[{"id":"10.13039\/https:\/\/doi.org\/10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2024,5,11]]},"DOI":"10.1145\/3613904.3642024","type":"proceedings-article","created":{"date-parts":[[2024,5,11]],"date-time":"2024-05-11T08:38:25Z","timestamp":1715416705000},"page":"1-20","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":62,"title":["Human-Algorithmic Interaction Using a Large Language Model-Augmented Artificial Intelligence Clinical Decision Support System"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1205-6979","authenticated-orcid":false,"given":"Niroop Channa","family":"Rajashekar","sequence":"first","affiliation":[{"name":"Yale School of Medicine, United States"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-2914-8328","authenticated-orcid":false,"given":"Yeo Eun","family":"Shin","sequence":"additional","affiliation":[{"name":"Yale School of Medicine, United States"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4227-1833","authenticated-orcid":false,"given":"Yuan","family":"Pu","sequence":"additional","affiliation":[{"name":"Yale School of Medicine, United States"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-5670-6664","authenticated-orcid":false,"given":"Sunny","family":"Chung","sequence":"additional","affiliation":[{"name":"Yale School of Medicine, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8584-459X","authenticated-orcid":false,"given":"Kisung","family":"You","sequence":"additional","affiliation":[{"name":"Mathematics, CUNY Baruch College, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9910-3514","authenticated-orcid":false,"given":"Mauro","family":"Giuffre","sequence":"additional","affiliation":[{"name":"Yale School of Medicine, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6323-5673","authenticated-orcid":false,"given":"Colleen E","family":"Chan","sequence":"additional","affiliation":[{"name":"Statistics and Data Science, Yale University, United States"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-2361-5557","authenticated-orcid":false,"given":"Theo","family":"Saarinen","sequence":"additional","affiliation":[{"name":"Department of Statistics, University of California, Berkeley, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8080-0002","authenticated-orcid":false,"given":"Allen","family":"Hsiao","sequence":"additional","affiliation":[{"name":"Pediatrics, Yale School of Medicine, United States"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-1218-0117","authenticated-orcid":false,"given":"Jasjeet","family":"Sekhon","sequence":"additional","affiliation":[{"name":"Statistics & Data Science, Yale University, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7471-1647","authenticated-orcid":false,"given":"Ambrose H","family":"Wong","sequence":"additional","affiliation":[{"name":"Yale University, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7118-7840","authenticated-orcid":false,"given":"Leigh V","family":"Evans","sequence":"additional","affiliation":[{"name":"Emergency Medicine, Yale School of Medicine, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6283-5546","authenticated-orcid":false,"given":"Rene F.","family":"Kizilcec","sequence":"additional","affiliation":[{"name":"Department of Information Science, Cornell University, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4296-7901","authenticated-orcid":false,"given":"Loren","family":"Laine","sequence":"additional","affiliation":[{"name":"Yale School of Medicine, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8143-5393","authenticated-orcid":false,"given":"Terika","family":"Mccall","sequence":"additional","affiliation":[{"name":"Division of Health Informatics, Department of Biostatistics, Yale School of Public Health, United States and Center for Medical Informatics, Yale School of Medicine, United States"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8226-1842","authenticated-orcid":false,"given":"Dennis","family":"Shung","sequence":"additional","affiliation":[{"name":"Yale School of Medicine, United States"}]}],"member":"320","published-online":{"date-parts":[[2024,5,11]]},"reference":[{"key":"e_1_3_3_3_1_1","unstructured":"Agency for Healthcare Research and Quality (AHRQ). 2019. Clinical Classifications Software (CCS) for ICD-10-PCS (Beta Version). Online software. https:\/\/hcup-us.ahrq.gov\/toolssoftware\/ccs10\/ccs10.jsp Accessed November."},{"key":"e_1_3_3_3_2_1","doi-asserted-by":"publisher","DOI":"10.4103\/1319-1683.68787"},{"key":"e_1_3_3_3_3_1","doi-asserted-by":"publisher","DOI":"10.1007\/s41666-019-00050-7"},{"key":"e_1_3_3_3_4_1","doi-asserted-by":"publisher","DOI":"10.3390\/app11115088"},{"key":"e_1_3_3_3_5_1","doi-asserted-by":"publisher","DOI":"10.1111\/medu.13883"},{"key":"e_1_3_3_3_6_1","doi-asserted-by":"publisher","DOI":"10.1186\/s12875-016-0490-3"},{"key":"e_1_3_3_3_7_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2019.12.012"},{"key":"e_1_3_3_3_8_1","doi-asserted-by":"publisher","DOI":"10.1001\/archinternmed.2009.215"},{"key":"e_1_3_3_3_9_1","first-page":"2697","article-title":"Simulation-based mastery learning reduces complications during central venous catheter insertion in a medical intensive care unit *","volume":"37","author":"Barsuk H.","year":"2009","unstructured":"Jeffrey\u00a0H. Barsuk, William\u00a0C. McGaghie, Elaine\u00a0R. Cohen, Kevin\u00a0J. O\u2019Leary, and Diane\u00a0B. Wayne. 2009. Simulation-based mastery learning reduces complications during central venous catheter insertion in a medical intensive care unit *. Critical Care Medicine 37, 10 (2009), 2697\u20132701. https:\/\/journals.lww.com\/ccmjournal\/fulltext\/2009\/10000\/simulation_based_mastery_learning_reduces.3.aspx","journal-title":"Critical Care Medicine"},{"key":"e_1_3_3_3_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376718"},{"key":"e_1_3_3_3_11_1","doi-asserted-by":"publisher","DOI":"10.1177\/0018720809336734"},{"key":"e_1_3_3_3_12_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.surg.2019.01.002"},{"key":"e_1_3_3_3_13_1","volume-title":"\u201cquick and dirty\u2019usability. Usability evaluation in industry 189, 3","author":"Brooke John","year":"1996","unstructured":"John Brooke. 1996. Sus: a \u201cquick and dirty\u2019usability. Usability evaluation in industry 189, 3 (1996), 189\u2013194."},{"key":"e_1_3_3_3_14_1","volume-title":"Language models are few-shot learners. Advances in neural information processing systems 33","author":"Brown Tom","year":"2020","unstructured":"Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared\u00a0D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, 2020. Language models are few-shot learners. Advances in neural information processing systems 33 (2020), 1877\u20131901."},{"key":"e_1_3_3_3_15_1","volume-title":"Retrieved","author":"Bruce Giles","year":"2023","unstructured":"Giles Bruce. 2023. Meditech, Google partner to bring generative AI to EHRs. Retrieved September 12, 2023 from https:\/\/www.beckershospitalreview.com\/digital-health\/meditech-google-partner-to-bring-generative-ai-to-ehrs.html"},{"key":"e_1_3_3_3_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300234"},{"key":"e_1_3_3_3_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3359206"},{"key":"e_1_3_3_3_18_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.mcna.2008.01.005"},{"key":"e_1_3_3_3_19_1","volume-title":"Retrieved","author":"Microsoft\u00a0News Center","year":"2023","unstructured":"Microsoft\u00a0News Center. 2023. Microsoft and Epic expand strategic collaboration with integration of Azure OpenAI Service. Retrieved September 12, 2023 from https:\/\/news.microsoft.com\/2023\/04\/17\/microsoft-and-epic-expand-strategic-collaboration-with-integration-of-azure-openai-service\/"},{"key":"e_1_3_3_3_20_1","unstructured":"Colleen Chan Kisung You Sunny Chung Mauro Giuffr\u00e8 Theo Saarinen Niroop Rajashekar Yuan Pu Yeo\u00a0Eun Shin Loren Laine Ambrose Wong Ren\u00e9 Kizilcec Jasjeet Sekhon and Dennis Shung. 2023. Assessing the Usability of GutGPT: A Simulation Study of an AI Clinical Decision Support System for Gastrointestinal Bleeding Risk. arxiv:2312.10072\u00a0[cs.HC]"},{"key":"e_1_3_3_3_21_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2023.27647"},{"key":"e_1_3_3_3_22_1","doi-asserted-by":"crossref","unstructured":"Cheng Chen. 2023. Is this AI trained on Credible Data? The Effects of Labeling Quality and Performance Bias on User Trust - CHI \u201923. https:\/\/programs.sigchi.org\/chi\/2023\/program\/content\/95899","DOI":"10.1145\/3544548.3580805"},{"key":"e_1_3_3_3_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939785"},{"key":"e_1_3_3_3_24_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2021.11.018"},{"key":"e_1_3_3_3_25_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-022-05112-2"},{"key":"e_1_3_3_3_26_1","doi-asserted-by":"publisher","DOI":"10.1136\/medethics-2020-106820"},{"key":"e_1_3_3_3_27_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10439-023-03329-4"},{"key":"e_1_3_3_3_28_1","doi-asserted-by":"publisher","DOI":"10.1136\/qhc.13.suppl_1.i2"},{"key":"e_1_3_3_3_29_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.293.10.1223"},{"key":"e_1_3_3_3_30_1","doi-asserted-by":"publisher","DOI":"10.1080\/1359432X.2023.2178904"},{"key":"e_1_3_3_3_31_1","doi-asserted-by":"publisher","DOI":"10.1097\/PTS.0000000000000598"},{"key":"e_1_3_3_3_32_1","doi-asserted-by":"publisher","DOI":"10.1126\/scirobotics.aay7120"},{"key":"e_1_3_3_3_33_1","unstructured":"Alison Hamilton. 2013. Qualitative Methods in Rapid Turn-Around Health Services Research. https:\/\/www.hsrd.research.va.gov\/for_researchers\/cyber_seminars\/archives\/video_archive.cfm?SessionID=780"},{"key":"e_1_3_3_3_34_1","unstructured":"UNC Health and UNC\u00a0School of Medicine. 2023. UNC Health Works with Epic on Integration of Generative Artificial Intelligence (AI) Tools. https:\/\/news.unchealthcare.org\/2023\/05\/unc-health-works-with-epic-on-integration-of-generative-artificial-intelligence-ai-tools\/ Accessed on November 2023."},{"key":"e_1_3_3_3_35_1","volume-title":"Human\u2013machine teaming is key to AI adoption: clinicians","author":"Henry E","year":"2022","unstructured":"Katharine\u00a0E Henry, Rachel Kornfield, Anirudh Sridharan, Robert\u00a0C Linton, Catherine Groh, Tony Wang, Albert Wu, Bilge Mutlu, and Suchi Saria. 2022. Human\u2013machine teaming is key to AI adoption: clinicians\u2019 experiences with a deployed machine learning system. NPJ digital medicine 5, 1 (2022), 97."},{"key":"e_1_3_3_3_36_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-022-00597-7"},{"key":"e_1_3_3_3_37_1","doi-asserted-by":"publisher","DOI":"10.4093\/jkd.2020.21.3.130"},{"key":"e_1_3_3_3_38_1","doi-asserted-by":"publisher","DOI":"10.4103\/0974-2700.70764"},{"key":"e_1_3_3_3_39_1","doi-asserted-by":"publisher","DOI":"10.1080\/01421590500046924"},{"key":"e_1_3_3_3_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445385"},{"key":"e_1_3_3_3_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445385"},{"key":"e_1_3_3_3_42_1","doi-asserted-by":"publisher","DOI":"10.1097\/MD.0000000000034068"},{"key":"e_1_3_3_3_43_1","doi-asserted-by":"publisher","DOI":"10.7759\/cureus.39305"},{"key":"e_1_3_3_3_44_1","doi-asserted-by":"publisher","DOI":"10.1001\/archinte.163.12.1409"},{"key":"e_1_3_3_3_45_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.tele.2022.101925"},{"key":"e_1_3_3_3_46_1","doi-asserted-by":"publisher","DOI":"10.1145\/2858036.2858402"},{"key":"e_1_3_3_3_47_1","doi-asserted-by":"publisher","DOI":"10.17226\/9728"},{"key":"e_1_3_3_3_48_1","volume-title":"Triage considerations for patients with acute gastrointestinal hemorrhage admitted to a medical intensive care unit. Critical care medicine 23, 6","author":"Kollef H","year":"1995","unstructured":"Marin\u00a0H Kollef, Denise\u00a0A Canfield, and Gary\u00a0R Zuckerman. 1995. Triage considerations for patients with acute gastrointestinal hemorrhage admitted to a medical intensive care unit. Critical care medicine 23, 6 (1995), 1048\u20131054."},{"key":"e_1_3_3_3_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/3582269.3615599"},{"key":"e_1_3_3_3_50_1","doi-asserted-by":"publisher","DOI":"10.1197\/jamia.M2170"},{"key":"e_1_3_3_3_51_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2004.01.003"},{"key":"e_1_3_3_3_52_1","volume-title":"ACG clinical guideline: upper gastrointestinal and ulcer bleeding. Official journal of the American College of Gastroenterology| ACG 116, 5","author":"Laine Loren","year":"2021","unstructured":"Loren Laine, Alan\u00a0N Barkun, John\u00a0R Saltzman, Myriam Martel, and Grigorios\u00a0I Leontiadis. 2021. ACG clinical guideline: upper gastrointestinal and ulcer bleeding. Official journal of the American College of Gastroenterology| ACG 116, 5 (2021), 899\u2013917."},{"key":"e_1_3_3_3_53_1","doi-asserted-by":"publisher","DOI":"10.1136\/amiajnl-2013-002233"},{"key":"e_1_3_3_3_54_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.leaqua.2019.101377"},{"key":"e_1_3_3_3_55_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cgh.2012.06.022"},{"key":"e_1_3_3_3_56_1","doi-asserted-by":"publisher","DOI":"10.3390\/informatics7030025"},{"key":"e_1_3_3_3_57_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2024.108013"},{"key":"e_1_3_3_3_58_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10439-023-03288-w"},{"key":"e_1_3_3_3_59_1","doi-asserted-by":"publisher","DOI":"10.3389\/fonc.2022.1003506"},{"key":"e_1_3_3_3_60_1","doi-asserted-by":"publisher","DOI":"10.2196\/jmir.8206"},{"key":"e_1_3_3_3_61_1","volume-title":"Zoie Shui-Yee Wong","author":"Magrabi Farah","year":"2019","unstructured":"Farah Magrabi, Elske Ammenwerth, Jytte\u00a0Brender McNair, Nicolet\u00a0F De\u00a0Keizer, Hannele Hypp\u00f6nen, Pirkko Nyk\u00e4nen, Michael Rigby, Philip\u00a0J Scott, Tuulikki Vehko, Zoie Shui-Yee Wong, 2019. Artificial intelligence in clinical decision support: challenges for evaluating AI and practical implications: a position paper from the IMIA Technology Assessment & Quality Development in Health Informatics Working Group and the EFMI Working Group for Assessment of Health Information Systems. Yearbook of medical informatics 28, 1 (2019), 128."},{"key":"e_1_3_3_3_62_1","doi-asserted-by":"publisher","DOI":"10.5603\/cj.a2018.0091"},{"key":"e_1_3_3_3_63_1","doi-asserted-by":"publisher","DOI":"10.1177\/2042098620968309"},{"key":"e_1_3_3_3_64_1","doi-asserted-by":"publisher","DOI":"10.1201\/b19082"},{"key":"e_1_3_3_3_65_1","doi-asserted-by":"publisher","DOI":"10.1093\/jamia"},{"key":"e_1_3_3_3_66_1","volume-title":"Medical diagnostic decision support systems\u2013past, present, and future: a threaded bibliography and brief commentary.Journal of the American Medical Informatics Association 1, 1","author":"Miller R\u00a0A","year":"1994","unstructured":"R\u00a0A Miller. 1994. Medical diagnostic decision support systems\u2013past, present, and future: a threaded bibliography and brief commentary.Journal of the American Medical Informatics Association 1, 1 (1994), 8\u201327. https:\/\/www.ncbi.nlm.nih.gov\/pmc\/articles\/PMC116181\/"},{"key":"e_1_3_3_3_67_1","doi-asserted-by":"publisher","DOI":"10.1093\/bib"},{"key":"e_1_3_3_3_68_1","doi-asserted-by":"publisher","DOI":"10.2105\/AJPH.2014.302164"},{"key":"e_1_3_3_3_69_1","unstructured":"Christoph Molnar. 2020. Interpretable machine learning. Lulu. com."},{"key":"e_1_3_3_3_70_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.amjmed.2011.07.029"},{"key":"e_1_3_3_3_71_1","unstructured":"OpenAI. 2022. Introducing ChatGPT. Retrieved September 5 2023 from https:\/\/openai.com\/research\/chatgpt"},{"key":"e_1_3_3_3_72_1","volume-title":"Improving outcomes with clinical decision support: an implementer\u2019s guide","author":"Osheroff A","unstructured":"Jerome\u00a0A Osheroff, Jonathan Teich, Donald Levick, Luis Saldana, Ferdinand Velasco, Dean Sittig, Kendall Rogers, and Robert Jenders. 2012. Improving outcomes with clinical decision support: an implementer\u2019s guide. Himss Publishing, Chicago, IL."},{"key":"e_1_3_3_3_73_1","doi-asserted-by":"publisher","DOI":"10.1197\/jamia.M2334"},{"key":"e_1_3_3_3_74_1","doi-asserted-by":"publisher","DOI":"10.1053\/j.gastro.2021.10.017"},{"key":"e_1_3_3_3_75_1","doi-asserted-by":"publisher","DOI":"10.7861\/clinmed.2019-0317"},{"key":"e_1_3_3_3_76_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamanetworkopen.2022.33946"},{"key":"e_1_3_3_3_77_1","doi-asserted-by":"publisher","DOI":"10.1111\/jgh.15384"},{"key":"e_1_3_3_3_78_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jinf.2023.07.011"},{"key":"e_1_3_3_3_79_1","unstructured":"Alec Radford Karthik Narasimhan Tim Salimans Ilya Sutskever 2018. Improving language understanding by generative pre-training. (2018)."},{"key":"e_1_3_3_3_80_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacr.2023.05.003"},{"key":"e_1_3_3_3_81_1","doi-asserted-by":"publisher","DOI":"10.2196\/48659"},{"key":"e_1_3_3_3_82_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1553-2712.2008.00180.x"},{"key":"e_1_3_3_3_83_1","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.326.7384.314"},{"key":"e_1_3_3_3_84_1","volume-title":"Learning representations by back-propagating errors. nature 323, 6088","author":"Rumelhart E","year":"1986","unstructured":"David\u00a0E Rumelhart, Geoffrey\u00a0E Hinton, and Ronald\u00a0J Williams. 1986. Learning representations by back-propagating errors. nature 323, 6088 (1986), 533\u2013536."},{"key":"e_1_3_3_3_85_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2020.103479"},{"key":"e_1_3_3_3_86_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2018.04.004"},{"key":"e_1_3_3_3_87_1","doi-asserted-by":"publisher","DOI":"10.3390\/healthcare11060887"},{"key":"e_1_3_3_3_88_1","doi-asserted-by":"publisher","DOI":"10.2196\/22421"},{"key":"e_1_3_3_3_89_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2017.04.018"},{"key":"e_1_3_3_3_90_1","doi-asserted-by":"publisher","DOI":"10.2337\/dc19-0587"},{"key":"e_1_3_3_3_91_1","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372827"},{"key":"e_1_3_3_3_92_1","doi-asserted-by":"publisher","DOI":"10.2196\/15182"},{"key":"e_1_3_3_3_93_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2018.17163"},{"key":"e_1_3_3_3_94_1","doi-asserted-by":"publisher","DOI":"10.1136\/jamia.2001.0080527"},{"key":"e_1_3_3_3_95_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-023-06291-2"},{"key":"e_1_3_3_3_96_1","doi-asserted-by":"publisher","DOI":"10.1097\/md.0000000000015995"},{"key":"e_1_3_3_3_97_1","doi-asserted-by":"publisher","DOI":"10.1038\/s41523-023-00557-8"},{"key":"e_1_3_3_3_98_1","doi-asserted-by":"publisher","DOI":"10.1186\/s13049-017-0425-6"},{"key":"e_1_3_3_3_99_1","doi-asserted-by":"publisher","DOI":"10.1126\/science.adg7879"},{"key":"e_1_3_3_3_100_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.2517-6161.1996.tb02080.x"},{"key":"e_1_3_3_3_101_1","volume-title":"Machine learning for healthcare conference. PMLR","author":"Tonekaboni Sana","unstructured":"Sana Tonekaboni, Shalmali Joshi, Melissa\u00a0D McCradden, and Anna Goldenberg. 2019. What clinicians want: contextualizing explainable machine learning for clinical end use. In Machine learning for healthcare conference. PMLR, University of Michigan, Ann Arbor, MI, 359\u2013380."},{"key":"e_1_3_3_3_102_1","unstructured":"U.S. Food and Drug Administration. 2017. Software as a Medical Device (SAMD): Clinical Evaluation Guidance for Industry and Food and Drug Administration Staff Food and Drug Administration Center for Devices and Radiological Health. https:\/\/www.fda.gov\/regulatory-information\/search-fda-guidance-documents\/software-medical-device-samd-clinical-evaluation"},{"key":"e_1_3_3_3_103_1","unstructured":"U.S. Food and Drug Administration. 2022. Clinical Decision Support Software - Guidance for Industry and Food and Drug Administration Staff. https:\/\/www.fda.gov\/regulatory-information\/search-fda-guidance-documents\/clinical-decision-support-software"},{"key":"e_1_3_3_3_104_1","doi-asserted-by":"publisher","DOI":"10.1197\/jamia.M1809"},{"key":"e_1_3_3_3_105_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.bpg.2007.10.011"},{"key":"e_1_3_3_3_106_1","doi-asserted-by":"publisher","DOI":"10.1111\/medu.14659"},{"key":"e_1_3_3_3_107_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-019-04051-w"},{"key":"e_1_3_3_3_108_1","doi-asserted-by":"publisher","DOI":"10.2307\/30036540"},{"key":"e_1_3_3_3_109_1","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2009.1677"},{"key":"e_1_3_3_3_110_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.2017.1319839"},{"key":"e_1_3_3_3_111_1","doi-asserted-by":"publisher","DOI":"10.1145\/3411764.3445432"},{"key":"e_1_3_3_3_112_1","doi-asserted-by":"publisher","DOI":"10.3389\/fcomp.2023.1187299"},{"key":"e_1_3_3_3_113_1","doi-asserted-by":"publisher","DOI":"10.1001\/archinte.163.21.2625"},{"key":"e_1_3_3_3_114_1","doi-asserted-by":"publisher","DOI":"10.1001\/jamainternmed.2021.2626"},{"key":"e_1_3_3_3_115_1","doi-asserted-by":"publisher","DOI":"10.1093\/jamia"},{"key":"e_1_3_3_3_116_1","doi-asserted-by":"publisher","DOI":"10.1145\/3290605.3300468"},{"key":"e_1_3_3_3_117_1","doi-asserted-by":"publisher","DOI":"10.1145\/3582430"},{"key":"e_1_3_3_3_118_1","doi-asserted-by":"publisher","DOI":"10.1016\/S1532-0464(03)00060-1"},{"key":"e_1_3_3_3_119_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbi.2011.08.005"},{"key":"e_1_3_3_3_120_1","doi-asserted-by":"publisher","DOI":"10.1101\/2023.06.10.23291127"}],"event":{"name":"CHI '24: CHI Conference on Human Factors in Computing Systems","location":"Honolulu HI USA","acronym":"CHI '24","sponsor":["SIGCHI ACM Special Interest Group on Computer-Human Interaction","SIGACCESS ACM Special Interest Group on Accessible Computing"]},"container-title":["Proceedings of the CHI Conference on Human Factors in Computing Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3613904.3642024","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3613904.3642024","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T23:57:30Z","timestamp":1750291050000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3613904.3642024"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,5,11]]},"references-count":120,"alternative-id":["10.1145\/3613904.3642024","10.1145\/3613904"],"URL":"https:\/\/doi.org\/10.1145\/3613904.3642024","relation":{},"subject":[],"published":{"date-parts":[[2024,5,11]]},"assertion":[{"value":"2024-05-11","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}