{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T06:57:14Z","timestamp":1772780234552,"version":"3.50.1"},"reference-count":155,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100001804","name":"Canada Research Chairs Program","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001804","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/access.2025.3648410","type":"journal-article","created":{"date-parts":[[2025,12,25]],"date-time":"2025-12-25T18:27:16Z","timestamp":1766687236000},"page":"1182-1212","source":"Crossref","is-referenced-by-count":1,"title":["Building Trustworthy AI in Healthcare"],"prefix":"10.1109","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-3282-8602","authenticated-orcid":false,"given":"Chimaobi","family":"Amadi","sequence":"first","affiliation":[{"name":"School of Information Technology, Carleton University, Ottawa, ON, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0565-2115","authenticated-orcid":false,"given":"Adegboyega","family":"Ojo","sequence":"additional","affiliation":[{"name":"School of Information Technology, Carleton University, Ottawa, ON, Canada"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3546872"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1016\/0010-4809(75)90009-9"},{"key":"ref3","first-page":"44","article-title":"CADUCEUS: A computerized diagnostic consultation system in internal medicine","volume-title":"Proc. Annu. Symp. Comput. Appl. Med. Care","author":"Myers"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1023\/A:1022643204877"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1023\/A:1016409317640"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1055\/s-0038-1634867"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1214\/ss\/1177010898"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/S0933-3657(01)00077-X"},{"issue":"4","key":"ref9","first-page":"362","article-title":"Artificial intelligence in medicine where do we stand?","volume":"27","author":"Schwartz","year":"1987","journal-title":"Jurimetrics"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03819-2"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.18203\/2349-3259.ijct20161408"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1097\/01.CCM.0000142394.28791.C3"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2023.106848"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3327905"},{"key":"ref15","article-title":"AI-driven healthcare: A review on ensuring fairness and mitigating bias","author":"Chinta","year":"2024","journal-title":"arXiv:2407.19655"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/B978-0-12-818438-7.00002-2","article-title":"The rise of artificial intelligence in healthcare applications","volume-title":"Artificial Intelligence in Healthcare","author":"Bohr","year":"2020"},{"key":"ref17","volume-title":"NHS to Trial AI Tool That Speeds Up Hospital Discharges","author":"Grierson","year":"2025"},{"key":"ref18","volume-title":"How AI Agents Are Redefining Intelligent Automation in the NHS","year":"2025"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1007\/s44250-022-00004-8"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3491209"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3577009"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-022-01984-6"},{"key":"ref23","article-title":"Creating trustworthy LLMs: Dealing with hallucinations in healthcare AI","author":"Ahmad","year":"2023","journal-title":"arXiv:2311.01463"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.imu.2025.101618"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2024.112374"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3555803"},{"key":"ref27","article-title":"AI safety landscape for large language models: Taxonomy, state-of-the-art, and future directions","author":"Chen","year":"2025","journal-title":"arXiv:2408.12935"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1186\/s12910-023-00917-w"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3675392"},{"key":"ref30","article-title":"Trustworthy AI must account for interactions","author":"Cresswell","year":"2025","journal-title":"arXiv:2504.07170"},{"key":"ref31","article-title":"TRiSM for agentic AI: A review of trust, risk, and security management in LLM-based agentic multi-agent systems","author":"Raza","year":"2025","journal-title":"arXiv:2506.04133"},{"key":"ref32","article-title":"Usable XAI: 10 strategies towards exploiting explainability in the LLM era","author":"Wu","year":"2024","journal-title":"arXiv:2403.08946"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3721976"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-76473-8_6"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/s44206-023-00062-2"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3645102"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ACIT62805.2024.10876871"},{"key":"ref38","volume-title":"Ethics and Governance of Artificial Intelligence for Health: WHO Guidance","year":"2021"},{"key":"ref39","volume-title":"Software as a Medical Device (SaMD): Key Definitions","year":"2013"},{"key":"ref40","volume-title":"Artificial Intelligence in Software as a Medical Device (SAMD)","year":"2024"},{"key":"ref41","volume-title":"Reflection Paper on the Use of Artificial Intelligence (AI) in the Medicinal Product Lifecycle","year":"2023"},{"key":"ref42","volume-title":"Software as a Medical Device (SAMD): Guidance Document","year":"2019"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/ieeestd.2022.9726144"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ieeestd.2021.9440873"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ieeestd.2025.10851955"},{"key":"ref46","first-page":"41","article-title":"Standard IEC 62304\u2013medical device software\u2013software lifecycle processes","volume-title":"Proc. IET Seminar Softw. Med. Devices","author":"Jordan"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1155\/2023\/4459198"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijmedinf.2024.105780"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-443-15299-3.00015-4"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TAI.2023.3266418"},{"key":"ref51","article-title":"Towards trustworthy AI: A review of ethical and robust large language models","author":"Meftahul Ferdaus","year":"2024","journal-title":"arXiv:2407.13934"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3294569"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-024-10868-x"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-023-02103-9"},{"key":"ref55","article-title":"Towards a unified utilitarian ethics framework for healthcare artificial intelligence","author":"Emdad","year":"2023","journal-title":"arXiv:2309.14617"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1186\/s12911-024-02653-6"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-52280-2_41"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-65434-3_3"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1609\/aaaiss.v4i1.31811"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2025.findings-emnlp.356"},{"key":"ref61","article-title":"A survey on medical large language models: Technology, application, trustworthiness, and future directions","author":"Liu","year":"2024","journal-title":"arXiv:2406.03712"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/ICIT63607.2024.10859641"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.9785\/cri-2019-200402"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-025-11389-2"},{"key":"ref65","article-title":"AI safety in generative AI large language models: A survey","author":"Chua","year":"2024","journal-title":"arXiv:2407.18369"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1007\/s41666-025-00196-7"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1007\/s44163-024-00129-0"},{"key":"ref68","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2024.108465"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-021-01595-0"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1186\/s12245-025-00975-4"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.3389\/fmed.2024.1331895"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.4314\/ahs.v23i2.86"},{"key":"ref73","first-page":"77","article-title":"Gender shades: Intersectional accuracy disparities in commercial gender classification","volume-title":"Proc. Conf. Fairness, Accountability Transparency","author":"Buolamwini"},{"key":"ref74","article-title":"Predictive inequity in object detection","author":"Wilson","year":"2019","journal-title":"arXiv:1902.11097"},{"key":"ref75","doi-asserted-by":"crossref","DOI":"10.1016\/j.csl.2023.101567","article-title":"Towards inclusive automatic speech recognition","volume":"84","author":"Feng","year":"2024","journal-title":"Comput. Speech Lang."},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1915768117"},{"key":"ref77","first-page":"15","article-title":"Gender bias in coreference resolution: Evaluation and debiasing methods","volume-title":"Proc. Conf. North Amer. Chapter Assoc. Comput. Linguistics, Human Lang. Technol.","author":"Zhao"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1145\/3461702.3462624"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1016\/S2589-7500(23)00225-X"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-025-03626-6"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/CCWC62904.2025.10903912"},{"key":"ref82","article-title":"The tug of war within: Mitigating the fairness-privacy conflicts in large language models","author":"Qian","year":"2024","journal-title":"arXiv:2410.16672"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1145\/3708821.3733888"},{"key":"ref84","article-title":"Towards trustworthy retrieval augmented generation for large language models: A survey","author":"Ni","year":"2025","journal-title":"arXiv:2502.06872"},{"key":"ref85","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-015-3794-0"},{"key":"ref86","doi-asserted-by":"publisher","DOI":"10.1126\/science.aaw4399"},{"key":"ref87","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1907377117"},{"key":"ref88","doi-asserted-by":"publisher","DOI":"10.1126\/science.1229566"},{"key":"ref89","first-page":"3043","article-title":"Reliable and trustworthy machine learning for health using dataset shift detection","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Park"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-15740-0_3"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2022.3197671"},{"key":"ref92","article-title":"Towards a rigorous science of interpretable machine learning","author":"Doshi-Velez","year":"2017","journal-title":"arXiv:1702.08608"},{"key":"ref93","first-page":"359","article-title":"What clinicians want: Contextualizing explainable machine learning for clinical end use","volume-title":"Proc. Mach. Learn. Healthcare Conf.","author":"Tonekaboni"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1016\/S2589-7500(21)00208-9"},{"key":"ref95","article-title":"Large language models in healthcare","author":"Al-Garadi","year":"2025","journal-title":"arXiv:2503.04748"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1109\/BigData62323.2024.10825008"},{"key":"ref97","doi-asserted-by":"publisher","DOI":"10.1109\/jbhi.2025.3558935"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1016\/j.smhl.2025.100552"},{"key":"ref99","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2025.3532853"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1109\/MIC.2023.3303031"},{"key":"ref101","article-title":"Trustworthy LLMs: A survey and guideline for evaluating large language models\u2019 alignment","author":"Liu","year":"2023","journal-title":"arXiv:2308.05374"},{"key":"ref102","article-title":"Fundamental limitations of alignment in large language models","author":"Wolf","year":"2023","journal-title":"arXiv:2304.11082"},{"key":"ref103","article-title":"Aligning large language models with human: A survey","author":"Wang","year":"2023","journal-title":"arXiv:2307.12966"},{"key":"ref104","first-page":"1","article-title":"DecodingTrust: A comprehensive assessment of trustworthiness in GPT models","volume-title":"Proc. NeurIPS","author":"Wang"},{"key":"ref105","article-title":"Medical hallucinations in foundation models and their impact on healthcare","author":"Kim","year":"2025","journal-title":"arXiv:2503.05777"},{"key":"ref106","doi-asserted-by":"publisher","DOI":"10.1186\/s13244-024-01616-9"},{"key":"ref107","doi-asserted-by":"publisher","DOI":"10.3389\/fcomp.2025.1570085"},{"key":"ref108","doi-asserted-by":"publisher","DOI":"10.1145\/3639372"},{"key":"ref109","article-title":"RARR: Researching and revising what language models say, using language models","author":"Gao","year":"2022","journal-title":"arXiv:2210.08726"},{"key":"ref110","first-page":"65468","article-title":"Post hoc explanations of language models can improve language models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Krishna"},{"key":"ref111","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.acl-main.386"},{"key":"ref112","first-page":"74952","article-title":"Language models don\u2019t always say what they think: Unfaithful explanations in chain-of-thought prompting","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"36","author":"Turpin"},{"key":"ref113","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3375624"},{"key":"ref114","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-019-0048-x"},{"key":"ref115","doi-asserted-by":"publisher","DOI":"10.2196\/59823"},{"key":"ref116","doi-asserted-by":"publisher","DOI":"10.1007\/s00330-025-11975-6"},{"key":"ref117","article-title":"Thoughts without thinking: Reconsidering the explanatory value of chain-of-thought reasoning in LLMs through agentic pipelines","author":"Manuvinakurike","year":"2025","journal-title":"arXiv:2505.00875"},{"key":"ref118","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2025.108599"},{"key":"ref119","doi-asserted-by":"publisher","DOI":"10.1109\/CSF.2017.11"},{"key":"ref120","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3301162"},{"key":"ref121","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmpb.2024.108289"},{"key":"ref122","doi-asserted-by":"publisher","DOI":"10.1145\/3689299.3689322"},{"key":"ref123","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-90026-6"},{"key":"ref124","first-page":"2668","article-title":"Interpretability beyond feature attribution: Quantitative testing with concept activation vectors (TCAV)","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Kim"},{"key":"ref125","first-page":"1","article-title":"Towards automatic concept-based explanations","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Ghorbani"},{"key":"ref126","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i19.30179"},{"key":"ref127","doi-asserted-by":"publisher","DOI":"10.1145\/3351095.3372852"},{"key":"ref128","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-025-02465-8"},{"key":"ref129","article-title":"A ChatGPT aided explainable framework for zero-shot medical image diagnosis","author":"Liu","year":"2023","journal-title":"arXiv:2307.01981"},{"key":"ref130","article-title":"A comprehensive study of knowledge editing for large language models","author":"Zhang","year":"2024","journal-title":"arXiv:2401.01286"},{"key":"ref131","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i27.35063"},{"key":"ref132","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2024.findings-acl.235"},{"key":"ref133","doi-asserted-by":"publisher","DOI":"10.52202\/079017-3910"},{"key":"ref134","doi-asserted-by":"publisher","DOI":"10.52202\/079017-3270"},{"key":"ref135","first-page":"9459","article-title":"Retrieval-augmented generation for knowledge-intensive NLP tasks","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Lewis"},{"key":"ref136","article-title":"Self-consistency improves chain of thought reasoning in language models","author":"Wang","year":"2022","journal-title":"arXiv:2203.11171"},{"key":"ref137","first-page":"46534","article-title":"Self-refine: Iterative refinement with self-feedback","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Madaan"},{"key":"ref138","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i24.34751"},{"key":"ref139","article-title":"DoLa: Decoding by contrasting layers improves factuality in large language models","author":"Chuang","year":"2023","journal-title":"arXiv:2309.03883"},{"key":"ref140","article-title":"VeriFact: Verifying facts in LLM-generated clinical text with electronic health records","author":"Chung","year":"2025","journal-title":"arXiv:2501.16672"},{"key":"ref141","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v39i26.34975"},{"key":"ref142","article-title":"Technical report on the CleverHans v2.1.0 adversarial examples library","volume-title":"arXiv:1610.00768","author":"Papernot","year":"2016"},{"key":"ref143","article-title":"Advertorch v0.1: An adversarial robustness toolbox based on PyTorch","author":"Weiguang Ding","year":"2019","journal-title":"arXiv:1902. 07623"},{"key":"ref144","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i18.18017"},{"key":"ref145","article-title":"RobustBench: A standardized adversarial robustness benchmark","author":"Croce","year":"2020","journal-title":"arXiv:2010.09670"},{"key":"ref146","article-title":"Practices for governing agentic AI systems","author":"Shavit","year":"2023"},{"key":"ref147","doi-asserted-by":"publisher","DOI":"10.1145\/3468264.3468565"},{"key":"ref148","article-title":"Inspecting and editing knowledge representations in language models","author":"Hernandez","year":"2023","journal-title":"arXiv:2304.00740"},{"key":"ref149","article-title":"Knowledge unlearning for mitigating privacy risks in language models","author":"Jang","year":"2022","journal-title":"arXiv:2210.01504"},{"key":"ref150","article-title":"Knowledge sanitization of large language models","author":"Ishibashi","year":"2023","journal-title":"arXiv:2309.11852"},{"key":"ref151","doi-asserted-by":"publisher","DOI":"10.1147\/JRD.2019.2942287"},{"key":"ref152","article-title":"Aequitas: A bias and fairness audit toolkit","author":"Saleiro","year":"2018","journal-title":"arXiv:1811.05577"},{"key":"ref153","doi-asserted-by":"publisher","DOI":"10.1145\/3464327.3464965"},{"key":"ref154","doi-asserted-by":"publisher","DOI":"10.1007\/s10207-025-01115-y"},{"key":"ref155","doi-asserted-by":"publisher","DOI":"10.1016\/j.imed.2021.10.001"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/11323511\/11315900.pdf?arnumber=11315900","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,6]],"date-time":"2026-01-06T05:38:48Z","timestamp":1767677928000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11315900\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":155,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3648410","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}