{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T01:19:55Z","timestamp":1767316795634,"version":"3.48.0"},"publisher-location":"Cham","reference-count":73,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032131669","type":"print"},{"value":"9783032131676","type":"electronic"}],"license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-13167-6_12","type":"book-chapter","created":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T01:16:13Z","timestamp":1767316573000},"page":"165-180","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["AI Systems for Physicians: A Review from Socio-technical and Human-Computer Interaction Perspectives"],"prefix":"10.1007","author":[{"given":"Jiaqi","family":"Wu Young","sequence":"first","affiliation":[]},{"given":"Fiona Fui-Hoon","family":"Nah","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,2]]},"reference":[{"key":"12_CR1","doi-asserted-by":"crossref","unstructured":"Olawade, D.B., David-Olawade, A.C., Wada, O.Z., Asaolu, A.J., Adereni, T., Ling, J.: Artificial intelligence in healthcare delivery: prospects and pitfalls.\u00a0J. Med. Surg. Pub. Health 3, Article 100108 (2024)","DOI":"10.1016\/j.glmedi.2024.100108"},{"key":"12_CR2","doi-asserted-by":"publisher","first-page":"1765","DOI":"10.2147\/IJGM.S449598","volume":"17","author":"A Shuaib","year":"2024","unstructured":"Shuaib, A.: Transforming healthcare with AI: promises, pitfalls, and pathways forward. Int. J. Gen. Med. 17, 1765\u20131771 (2024)","journal-title":"Int. J. Gen. Med."},{"key":"12_CR3","unstructured":"Goldsack, J., Overgaard, S.: Billions of dollars have been invested in healthcare AI. But are we spending in the right places?\u00a0World Econ. Forum\u00a0(2024). https:\/\/www.weforum.org\/stories\/2024\/11\/healthcare-health-ai\/"},{"key":"12_CR4","unstructured":"Heaven, W.D.: Google\u2019s medical AI was super accurate in a lab. Real life was a different story.\u00a0MIT Technol. Rev.\u00a0(2020), https:\/\/www.technologyreview.com\/2020\/04\/27\/1000658\/google-medical-ai-accurate-lab-%20real-life-clinic-covid-diabetes-retina-disease\/"},{"issue":"3","key":"12_CR5","doi-asserted-by":"publisher","first-page":"17","DOI":"10.2307\/248710","volume":"1","author":"RP Bostrom","year":"1977","unstructured":"Bostrom, R.P., Heinen, J.S.: MIS problems and failures: a socio-technical perspective, part I: the causes. MIS Q. 1(3), 17\u201332 (1977)","journal-title":"MIS Q."},{"key":"12_CR6","unstructured":"European Parliament and Council.: Regulation (EU) 2024\/1689 of 12 July 2024 on laying down harmonised rules on artificial intelligence (Artificial Intelligence Act) and amending certain Union legislative acts.\u00a0Official J. Eur. Union\u00a0(2024)"},{"key":"12_CR7","unstructured":"U.S. Food and Drug Administration: Artificial Intelligence\/Machine Learning (AI\/ML)-Based Software as a Medical Device (SaMD) Action Plan. https:\/\/www.fda.gov\/media\/145022\/download. Accessed 22 Mar 2024"},{"key":"12_CR8","doi-asserted-by":"crossref","unstructured":"Addas, S.: A call for engaging context in HCI\/MIS research with examples from the area of technology interruptions. AIS Trans. Hum.-Comput. Interact. 2(4), 178\u2013196 (2010)","DOI":"10.17705\/1thci.00022"},{"issue":"2","key":"12_CR9","doi-asserted-by":"publisher","first-page":"386","DOI":"10.5465\/amr.2006.20208687","volume":"31","author":"G Johns","year":"2006","unstructured":"Johns, G.: The essential impact of context on organizational behavior. Acad. Manag. Rev. 31(2), 386\u2013408 (2006)","journal-title":"Acad. Manag. Rev."},{"issue":"1","key":"12_CR10","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1146\/annurev-orgpsych-032117-104406","volume":"5","author":"G Johns","year":"2018","unstructured":"Johns, G.: Advances in the treatment of context in organizational research. Annu. Rev. Organ. Psychol. Organ. Behav. 5(1), 21\u201346 (2018)","journal-title":"Annu. Rev. Organ. Psychol. Organ. Behav."},{"issue":"1","key":"12_CR11","first-page":"17","volume":"121","author":"JH Holland","year":"1992","unstructured":"Holland, J.H.: Complex adaptive systems. Daedalus 121(1), 17\u201330 (1992)","journal-title":"Daedalus"},{"issue":"4","key":"12_CR12","doi-asserted-by":"publisher","first-page":"515","DOI":"10.5465\/amr.2012.0099","volume":"40","author":"FP Morgeson","year":"2015","unstructured":"Morgeson, F.P., Mitchell, T.R., Liu, D.: Event system theory: an event-oriented approach to the organizational sciences. Acad. Manag. Rev. 40(4), 515\u2013537 (2015)","journal-title":"Acad. Manag. Rev."},{"issue":"Suppl 3","key":"12_CR13","doi-asserted-by":"publisher","first-page":"i68","DOI":"10.1136\/qshc.2010.042085","volume":"19","author":"DF Sittig","year":"2010","unstructured":"Sittig, D.F., Singh, H.: A new socio-technical model for studying health information technology in complex adaptive healthcare systems. Qual. Saf. Health Care 19(Suppl 3), i68\u2013i74 (2010)","journal-title":"Qual. Saf. Health Care"},{"key":"12_CR14","volume-title":"Systems Thinking: Managing Chaos and Complexity \u2013 A Platform for Designing Business Architecture","author":"J Gharajedaghi","year":"2011","unstructured":"Gharajedaghi, J.: Systems Thinking: Managing Chaos and Complexity \u2013 A Platform for Designing Business Architecture, 3rd edn. Elsevier, Amsterdam (2011)","edition":"3"},{"key":"12_CR15","unstructured":"International Organization for Standardization: ISO\/IEC 22989:2022 Artificial Intelligence\u2014Concepts and Terminology. ISO, Geneva (2022)"},{"issue":"1","key":"12_CR16","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1109\/MIS.2017.1","volume":"32","author":"D Danks","year":"2017","unstructured":"Danks, D., London, A.J.: Regulating autonomous systems: beyond standards. IEEE Intell. Syst. 32(1), 88\u201391 (2017)","journal-title":"IEEE Intell. Syst."},{"key":"12_CR17","volume-title":"Making Things Work: Solving Complex Problems in a Complex World","author":"Y Bar-Yam","year":"2004","unstructured":"Bar-Yam, Y.: Making Things Work: Solving Complex Problems in a Complex World. NECSI Knowledge Press, Cambridge (2004)"},{"key":"12_CR18","unstructured":"Organization for Economic Co-operation and Development: Explanatory memorandum on the updated OECD definition of an AI system. https:\/\/www.oecd.org\/content\/dam\/oecd\/en\/publications\/reports\/2024\/03\/explanatory-memorandum-on-the-updated-oecd-definition-of-an-ai-system_3c815e51\/623da898-en.pdf"},{"issue":"2","key":"12_CR19","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1038\/s41591-021-01229-5","volume":"27","author":"DECIDE-AI Steering Group","year":"2021","unstructured":"DECIDE-AI Steering Group: DECIDE-AI: New reporting guidelines to bridge the development-to-implementation gap in clinical artificial intelligence. Nat. Med. 27(2), 186\u2013187 (2021)","journal-title":"Nat. Med."},{"key":"12_CR20","doi-asserted-by":"crossref","unstructured":"Wang, L., et al.: Human-centered design and evaluation of AI-empowered clinical decision support systems: a systematic review. Front. Comput. Sci. 5, Article 108 (2023)","DOI":"10.3389\/fcomp.2023.1187299"},{"issue":"11","key":"12_CR21","doi-asserted-by":"publisher","first-page":"e745","DOI":"10.1016\/S2589-7500(21)00208-9","volume":"3","author":"M Ghassemi","year":"2021","unstructured":"Ghassemi, M., Oakden-Rayner, L., Beam, A.L.: The false hope of current approaches to explainable artificial intelligence in health care. Lancet Digit. Health 3(11), e745\u2013e750 (2021)","journal-title":"Lancet Digit. Health"},{"issue":"1","key":"12_CR22","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1518\/hfes.46.1.50.30392","volume":"46","author":"JD Lee","year":"2004","unstructured":"Lee, J.D., See, K.A.: Trust in automation: designing for appropriate reliance. Hum. Factors 46(1), 50\u201380 (2004)","journal-title":"Hum. Factors"},{"key":"12_CR23","doi-asserted-by":"crossref","unstructured":"Madhavan, P., Wiegmann, D.A.: A new look at the dynamics of human-automation trust: Is trust in humans comparable to trust in machines? Proc. Hum. Factors Ergon. Soc. Annu. Meet. 48(3), 582\u2013586 (2004)","DOI":"10.1177\/154193120404800365"},{"issue":"2","key":"12_CR24","first-page":"202","volume":"35","author":"M Farjoun","year":"2010","unstructured":"Farjoun, M.: Beyond dualism: Stability and change as a duality. Acad. Manag. Rev. 35(2), 202\u2013225 (2010)","journal-title":"Acad. Manag. Rev."},{"issue":"2","key":"12_CR25","first-page":"381","volume":"36","author":"WK Smith","year":"2011","unstructured":"Smith, W.K., Lewis, M.W.: Toward a theory of paradox: a dynamic equilibrium model of organizing. Acad. Manag. Rev. 36(2), 381\u2013403 (2011)","journal-title":"Acad. Manag. Rev."},{"key":"12_CR26","unstructured":"Scott, W.R.: Institutions and Organizations: Ideas and Interests, 3rd edn. SAGE, Thousand Oaks (2008)"},{"key":"12_CR27","doi-asserted-by":"crossref","unstructured":"Woods, W., Grushin, A., Khan, S., Velasquez, A.: Combining AI control systems and human decision support via robustness and criticality. Manuscript in preparation (2024)","DOI":"10.1117\/12.3016311"},{"key":"12_CR28","volume-title":"Safety-I and Safety-II: The Past and Future of Safety Management","author":"E Hollnagel","year":"2014","unstructured":"Hollnagel, E.: Safety-I and Safety-II: The Past and Future of Safety Management. CRC Press, Boca Raton (2014)"},{"issue":"5","key":"12_CR29","doi-asserted-by":"publisher","first-page":"1123","DOI":"10.1287\/orsc.1100.0621","volume":"22","author":"L Argote","year":"2011","unstructured":"Argote, L., Miron-Spektor, E.: Organizational learning: from experience to knowledge. Organ. Sci. 22(5), 1123\u20131137 (2011)","journal-title":"Organ. Sci."},{"issue":"3","key":"12_CR30","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1007\/s10140-023-02121-0","volume":"30","author":"A Agrawal","year":"2023","unstructured":"Agrawal, A., Khatri, G.D., Khurana, B., Sodickson, A.D., Liang, Y., Dreizin, D.: A survey of ASER members on artificial intelligence in emergency radiology: trends, perceptions, and expectations. Emerg. Radiol. 30(3), 267\u2013277 (2023)","journal-title":"Emerg. Radiol."},{"issue":"7","key":"12_CR31","doi-asserted-by":"publisher","first-page":"846","DOI":"10.1097\/PAS.0000000000002248","volume":"48","author":"JA Retamero","year":"2024","unstructured":"Retamero, J.A., et al.: Artificial intelligence helps pathologists increase diagnostic accuracy and efficiency in the detection of breast cancer lymph node metastases. Am. J. Surg. Pathol. 48(7), 846\u2013854 (2024)","journal-title":"Am. J. Surg. Pathol."},{"issue":"10","key":"12_CR32","doi-asserted-by":"publisher","first-page":"1684","DOI":"10.1093\/jamia\/ocad118","volume":"30","author":"DY Wang","year":"2023","unstructured":"Wang, D.Y., et al.: Artificial intelligence suppression as a strategy to mitigate artificial intelligence automation bias. J. Am. Med. Inform. Assoc. 30(10), 1684\u20131692 (2023)","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"12_CR33","doi-asserted-by":"crossref","unstructured":"Jansson, M., et al.: Artificial intelligence-enhanced care pathway planning and scheduling system: content validity assessment of required functionalities. BMC Health Serv. Res. 22(1), Article 1513 (2022)","DOI":"10.1186\/s12913-022-08780-y"},{"key":"12_CR34","doi-asserted-by":"crossref","unstructured":"Jung, M., et al.: Augmented interpretation of HER2, ER, and PR in breast cancer by artificial intelligence analyzer: enhancing interobserver agreement through a reader study of 201 cases. Breast Cancer Res. 26(1), Article 31 (2024)","DOI":"10.1186\/s13058-024-01784-y"},{"key":"12_CR35","doi-asserted-by":"crossref","unstructured":"Zaj\u0105c, H. D., Li, D., Dai, X., Carlsen, J. F., Kensing, F., Andersen, T. O.: Clinician-facing AI in the wild: taking stock of the sociotechnical challenges and opportunities for HCI. ACM Trans. Comput.-Hum. Interact. 30(2), Article 33 (2023)","DOI":"10.1145\/3582430"},{"issue":"7","key":"12_CR36","doi-asserted-by":"publisher","first-page":"e507","DOI":"10.1016\/S2589-7500(22)00070-X","volume":"4","author":"C Leibig","year":"2022","unstructured":"Leibig, C., Brehmer, M., Bunk, S., Byng, D., Pinker, K., Umutlu, L.: Combining the strengths of radiologists and AI for breast cancer screening: a retrospective analysis. Lancet Digit. Health 4(7), e507\u2013e519 (2022)","journal-title":"Lancet Digit. Health"},{"key":"12_CR37","doi-asserted-by":"crossref","unstructured":"Frazer, H.M.L., et al.: Comparison of AI-integrated pathways with human-AI interaction in population mammographic screening for breast cancer. Nat. Commun. 15(1), Article 7525 (2024)","DOI":"10.1038\/s41467-024-51725-8"},{"key":"12_CR38","doi-asserted-by":"crossref","unstructured":"Thieme, A., et al.: Designing human-centered AI for mental health: developing clinically relevant applications for online CBT treatment. ACM Trans. Comput.-Hum. Interact. 30(2), Article 27 (2023)","DOI":"10.1145\/3564752"},{"key":"12_CR39","doi-asserted-by":"crossref","unstructured":"Carmichael, J., Costanza, E., Blandford, A., Struyven, R., Keane, P.A., Balaskas, K.: Diagnostic decisions of specialist optometrists exposed to ambiguous deep-learning outputs. Sci. Rep. 14(1), Article 6775 (2024)","DOI":"10.1038\/s41598-024-55410-0"},{"key":"12_CR40","unstructured":"Kritharidou, M., et al.: Ethicara for responsible AI in healthcare: a system for bias detection and AI risk management. In: AMIA Annual Symposium Proceedings 2023, pp. 2023\u20132032 (2023)"},{"key":"12_CR41","doi-asserted-by":"crossref","unstructured":"Novak, A., et al.: Evaluating the impact of artificial intelligence-assisted image analysis on the diagnostic accuracy of front-line clinicians in detecting fractures on plain X-rays (FRACT-AI): protocol for a prospective observational study. BMJ Open 14(9), e086061 (2024)","DOI":"10.1136\/bmjopen-2024-086061"},{"key":"12_CR42","doi-asserted-by":"crossref","unstructured":"Famiglini, L., Campagner, A., Barandas, M., La Maida, G.A., Gallazzi, E., Cabitza, F.: Evidence-based XAI: an empirical approach to design more effective and explainable decision support systems. Comput. Biol. Med. 170, Article 108042 (2024)","DOI":"10.1016\/j.compbiomed.2024.108042"},{"key":"12_CR43","doi-asserted-by":"crossref","unstructured":"Reverberi, C., et al.: Experimental evidence of effective human-AI collaboration in medical decision-making. Sci. Rep. 12(1), Article 14952 (2022)","DOI":"10.1038\/s41598-022-18751-2"},{"key":"12_CR44","doi-asserted-by":"crossref","unstructured":"Gomez, C., Smith, B.L., Zayas, A., Unberath, M., Canares, T.: Explainable AI decision support improves accuracy during telehealth strep throat screening. Commun. Med. 4(1), Article 149 (2024)","DOI":"10.1038\/s43856-024-00568-x"},{"key":"12_CR45","doi-asserted-by":"crossref","unstructured":"Nagendran, M., Festor, P., Komorowski, M., Gordon, A.C., Faisal, A.A.: Eye tracking insights into physician behaviour with safe and unsafe explainable AI recommendations. NPJ Digit. Med. 7(1), Article 202 (2024)","DOI":"10.1038\/s41746-024-01200-x"},{"key":"12_CR46","doi-asserted-by":"crossref","unstructured":"Ghosh, P., et al.: Framing machine learning opportunities for hypotension prediction in perioperative care: A socio-technical perspective. ACM Trans. Comput.-Hum. Interact. 30(5), Article 79 (2023)","DOI":"10.1145\/3589953"},{"key":"12_CR47","doi-asserted-by":"crossref","unstructured":"de Hond, A.A.H., et al.: Guidelines and quality criteria for artificial intelligence-based prediction models in healthcare: a scoping review. NPJ Digit. Med. 5(1), Article 2 (2022)","DOI":"10.1038\/s41746-021-00549-7"},{"key":"12_CR48","doi-asserted-by":"crossref","unstructured":"Procter, R., Tolmie, P., Rouncefield, M.: Holding AI to account: challenges for the delivery of trustworthy AI in healthcare. ACM Trans. Comput.-Hum. Interact. 30(2), Article 31 (2023)","DOI":"10.1145\/3577009"},{"issue":"1","key":"12_CR49","doi-asserted-by":"publisher","first-page":"e28639","DOI":"10.2196\/28639","volume":"9","author":"M Knop","year":"2022","unstructured":"Knop, M., Weber, S., Mueller, M., Niehaves, B.: Human factors and technological characteristics influencing the interaction of medical professionals with artificial intelligence-enabled clinical decision support systems: literature review. JMIR Hum. Factors 9(1), e28639 (2022)","journal-title":"JMIR Hum. Factors"},{"key":"12_CR50","doi-asserted-by":"crossref","unstructured":"Krakowski, I., et al.: Human-AI interaction in skin cancer diagnosis: a systematic review and meta-analysis. NPJ Digit. Med. 7(1), Article 78 (2024)","DOI":"10.1038\/s41746-024-01031-w"},{"issue":"3","key":"12_CR51","doi-asserted-by":"publisher","first-page":"126","DOI":"10.4253\/wjge.v16.i3.126","volume":"16","author":"JR Campion","year":"2024","unstructured":"Campion, J.R., O\u2019Connor, D.B., Lahiff, C.: Human-artificial intelligence interaction in gastrointestinal endoscopy. World J. Gastrointest. Endosc. 16(3), 126\u2013135 (2024)","journal-title":"World J. Gastrointest. Endosc."},{"key":"12_CR52","doi-asserted-by":"crossref","unstructured":"Tahri Sqalli, M., Aslonov, B., Gafurov, M., Nurmatov, S.: Humanizing AI in medical training: ethical framework for responsible design. Front. Artif. Intell. 6, Article 1189914 (2023)","DOI":"10.3389\/frai.2023.1189914"},{"issue":"5","key":"12_CR53","doi-asserted-by":"publisher","first-page":"857","DOI":"10.5009\/gnl240068","volume":"18","author":"J Lee","year":"2024","unstructured":"Lee, J., et al.: Impact of user\u2019s background knowledge and polyp characteristics in colonoscopy with computer-aided detection. Gut Liver 18(5), 857\u2013866 (2024)","journal-title":"Gut Liver"},{"key":"12_CR54","doi-asserted-by":"crossref","unstructured":"Gu, H., et al.: Improving workflow integration with xPath: design and evaluation of a human-AI diagnosis system in pathology. ACM Trans. Comput.-Hum. Interact. 30(2), Article 28 (2023)","DOI":"10.1145\/3577011"},{"issue":"5","key":"12_CR55","doi-asserted-by":"publisher","first-page":"e2313674","DOI":"10.1001\/jamanetworkopen.2023.13674","volume":"6","author":"WJ Tong","year":"2023","unstructured":"Tong, W.J., et al.: Integration of artificial intelligence decision aids to reduce workload and enhance efficiency in thyroid nodule management. JAMA Netw. Open 6(5), e2313674 (2023)","journal-title":"JAMA Netw. Open"},{"key":"12_CR56","doi-asserted-by":"crossref","unstructured":"Zhang, J., Wu, J., Qiu, Y., Song, A., Li, W., Li, X., Liu, Y.: Intelligent speech technologies for transcription, disease diagnosis, and medical equipment interactive control in smart hospitals: a review. Comput. Biol. Med. 153, Article 106517 (2023)","DOI":"10.1016\/j.compbiomed.2022.106517"},{"key":"12_CR57","doi-asserted-by":"crossref","unstructured":"C\u00e1lem, J., Moreira, C., Jorge, J.: Intelligent systems in healthcare: a systematic survey of explainable user interfaces. Comput. Biol. Med. 180, Article 108908 (2024)","DOI":"10.1016\/j.compbiomed.2024.108908"},{"key":"12_CR58","doi-asserted-by":"crossref","unstructured":"Xu, Q., et al.: Interpretability of clinical decision support systems based on artificial intelligence from technological and medical perspective: a systematic review. J. Healthc. Eng. 2023, Article 9919269 (2023)","DOI":"10.1155\/2023\/9919269"},{"key":"12_CR59","doi-asserted-by":"crossref","unstructured":"van Berkel, N., Bellio, M., Skov, M.B., Blandford, A.: Measurements, algorithms, and presentations of reality: framing interactions with AI-enabled decision support. ACM Trans. Comput.-Hum. Interact. 30(2), Article 32 (2023)","DOI":"10.1145\/3571815"},{"key":"12_CR60","doi-asserted-by":"crossref","unstructured":"Adam, H., Balagopalan, A., Alsentzer, E., Christia, F., Ghassemi, M.: Mitigating the impact of biased artificial intelligence in emergency decision-making. Commun. Med. 2(1), Article 149 (2022)","DOI":"10.1038\/s43856-022-00214-4"},{"issue":"1","key":"12_CR61","doi-asserted-by":"publisher","first-page":"e41940","DOI":"10.2196\/41940","volume":"1","author":"B Barry","year":"2022","unstructured":"Barry, B., et al.: Provider perspectives on artificial intelligence-guided screening for low ejection fraction in primary care: qualitative study. JMIR AI 1(1), e41940 (2022)","journal-title":"JMIR AI"},{"key":"12_CR62","doi-asserted-by":"crossref","unstructured":"Duncan, S.F., et al.: Radiograph accelerated detection and identification of cancer in the lung (RADICAL): a mixed methods study to assess the clinical effectiveness and acceptability of Qure.ai artificial intelligence software to prioritise chest X-ray (CXR) interpretation. BMJ Open 14(9), e081062 (2024)","DOI":"10.1136\/bmjopen-2023-081062"},{"key":"12_CR63","doi-asserted-by":"publisher","first-page":"107924","DOI":"10.1016\/j.compbiomed.2024.107924","volume":"169","author":"J Yang","year":"2024","unstructured":"Yang, J., et al.: RDmaster: a novel phenotype-oriented dialogue system supporting differential diagnosis of rare disease. Comput. Biol. Med. 169, 107924 (2024)","journal-title":"Comput. Biol. Med."},{"issue":"8","key":"12_CR64","doi-asserted-by":"publisher","first-page":"5415","DOI":"10.1007\/s00330-023-10514-5","volume":"34","author":"H Al-Bazzaz","year":"2024","unstructured":"Al-Bazzaz, H., Janicijevic, M., Strand, F.: Reader bias in breast cancer screening related to cancer prevalence and artificial intelligence decision support\u2014a reader study. Eur. Radiol. 34(8), 5415\u20135424 (2024)","journal-title":"Eur. Radiol."},{"issue":"1","key":"12_CR65","doi-asserted-by":"publisher","first-page":"6897","DOI":"10.1038\/s41467-024-50954-1","volume":"15","author":"C Wies","year":"2024","unstructured":"Wies, C., Hauser, K., Brinker, T.J.: Reply to: False conflict and false confirmation errors are crucial components of AI accuracy in medical decision making. Nat. Commun. 15(1), 6897 (2024)","journal-title":"Nat. Commun."},{"key":"12_CR66","doi-asserted-by":"publisher","first-page":"e50295","DOI":"10.2196\/50295","volume":"26","author":"C S\u00e1ez","year":"2024","unstructured":"S\u00e1ez, C., Ferri, P., Garc\u00eda-G\u00f3mez, J.M.: Resilient artificial intelligence in health: synthesis and research agenda toward next-generation trustworthy clinical decision support. J. Med. Internet Res. 26, e50295 (2024)","journal-title":"J. Med. Internet Res."},{"key":"12_CR67","doi-asserted-by":"crossref","unstructured":"Zhang, S., et al.: Rethinking human-AI collaboration in complex medical decision making: a case study in sepsis diagnosis. Proc. CHI Conf. Hum. Factors Comput. Syst., Article 445 (2024)","DOI":"10.1145\/3613904.3642343"},{"key":"12_CR68","doi-asserted-by":"publisher","first-page":"106668","DOI":"10.1016\/j.compbiomed.2023.106668","volume":"156","author":"S Nazir","year":"2023","unstructured":"Nazir, S., Dickson, D.M., Akram, M.U.: Survey of explainable artificial intelligence techniques for biomedical imaging with deep neural networks. Comput. Biol. Med. 156, 106668 (2023)","journal-title":"Comput. Biol. Med."},{"key":"12_CR69","doi-asserted-by":"publisher","first-page":"107071","DOI":"10.1016\/j.compbiomed.2023.107071","volume":"162","author":"J Hern\u00e1ndez-Aceituno","year":"2023","unstructured":"Hern\u00e1ndez-Aceituno, J., M\u00e9ndez-P\u00e9rez, J.A., Gonz\u00e1lez-Cava, J.M., Reboso-Morales, J.A.: Towards intelligent supervision of operating rooms using stencil-based character recognition. Comput. Biol. Med. 162, 107071 (2023)","journal-title":"Comput. Biol. Med."},{"key":"12_CR70","volume-title":"Managing the Unexpected: Resilient Performance in an Age of Uncertainty","author":"KE Weick","year":"2007","unstructured":"Weick, K.E., Sutcliffe, K.M.: Managing the Unexpected: Resilient Performance in an Age of Uncertainty, 2nd edn. Jossey-Bass, San Francisco (2007)","edition":"2"},{"key":"12_CR71","unstructured":"Williams, B.K., Brown, E.D.: Adaptive Management: The U.S. Department of the Interior Technical Guide. U.S. Department of the Interior, Washington D.C. (2012)"},{"key":"12_CR72","volume-title":"Feedback Systems: An Introduction for Scientists and Engineers","author":"KJ \u00c5str\u00f6m","year":"2008","unstructured":"\u00c5str\u00f6m, K.J., Murray, R.M.: Feedback Systems: An Introduction for Scientists and Engineers. Princeton University Press, Princeton (2008)"},{"issue":"1","key":"12_CR73","doi-asserted-by":"publisher","first-page":"61","DOI":"10.2307\/2393551","volume":"35","author":"SR Barley","year":"1990","unstructured":"Barley, S.R.: The alignment of technology and structure through roles and networks. Adm. Sci. Q. 35(1), 61\u2013103 (1990)","journal-title":"Adm. Sci. Q."}],"container-title":["Lecture Notes in Computer Science","HCI International 2025 \u2013 Late Breaking Papers"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-13167-6_12","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T01:16:19Z","timestamp":1767316579000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-13167-6_12"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"ISBN":["9783032131669","9783032131676"],"references-count":73,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-13167-6_12","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"2 January 2026","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"HCII","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Human-Computer Interaction","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Gothenburg","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sweden","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 June 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 June 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"hcii2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2025.hci.international\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}