Research graph
References from Participatory Design of AI-Based Clinical Decision Support Systems: Scoping Review. Local targets link to admitted publications; unresolved targets remain external evidence.
Effects of clinical decision-support systems on practitioner performance and patient outcomes: a synthesis of high-quality systematic review findings
10.1136/amiajnl-2011-000094 · External reference
Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success
10.1136/bmj.38398.500764.8f · External reference
Improved guideline adherence in oncology through clinical decision-support systems: still hindered by current health IT infrastructures?
10.1097/cco.0000000000000916 · External reference
Artificial intelligence in healthcare
10.1038/s41551-018-0305-z · External reference
Big data analytics for preventive medicine
10.1007/s00521-019-04095-y · External reference
Questions for artificial intelligence in health care
10.1001/jama.2018.18932 · External reference
A sociotechnical systems framework for the application of artificial intelligence in health care delivery
10.1177/15553434221097357 · External reference
Application scenarios for artificial intelligence in nursing care: rapid review
10.2196/26522 · External reference
Exploring needs and challenges for AI in nursing care – results of an explorative sequential mixed methods study
10.1186/s44247-023-00015-2 · External reference
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10.1145/3551624.3555290
10.1145/3551624.3555290 · External reference
10.1145/3384772.3385138
10.1145/3384772.3385138 · External reference
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Co-creation and the new landscapes of design
10.1080/15710880701875068 · External reference
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Participatory research methods: a methodological approach in motion
10.17169/fqs-13.1.1801 · External reference
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Participatory design of an AI-Based CDSS for delirium prevention
10.3233/shti250357 · External reference
A ladder of citizen participation
10.1080/01944366908977225 · External reference
10.1145/2470654.2470716
10.1145/2470654.2470716 · External reference
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Challenges and facilitation approaches for the participatory design of AI-based clinical decision support systems: protocol for a scoping review
10.2196/58185 · External reference
PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation
10.7326/m18-0850 · External reference
Envisioning an artificial intelligence documentation assistant for future primary care consultations: a co-design study with general practitioners
10.1093/jamia/ocaa131 · External reference
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Categorizing methods used in participatory research
10.1007/s00103-020-03267-9 · External reference
Participatory methods to engage health service users in the development of electronic health resources: systematic review
10.2196/11474 · External reference
10.1145/3322276.3323697
10.1145/3322276.3323697 · External reference
Guidance for conducting systematic scoping reviews
10.1097/xeb.0000000000000050 · External reference
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Welcome to implementation science
10.1186/1748-5908-1-1 · External reference
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ImageNet classification with deep convolutional neural networks
10.1145/3065386 · External reference
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Using a simulation centre to evaluate preliminary acceptability and impact of an artificial intelligence-powered clinical decision support system for depression treatment on the physician-patient interaction
10.1192/bjo.2020.127 · External reference
10.1145/3411764.3445472
10.1145/3411764.3445472 · External reference
Requirements analysis for an AI-based clinical decision support system for general practitioners: a user-centered design process
10.1186/s12911-023-02245-w · External reference
Designing a mHealth clinical decision support system for Parkinson’s disease: a theoretically grounded user needs approach
10.1186/s12911-020-1027-1 · External reference
Designing visual markers for continuous artificial intelligence support
10.1145/3422156 · External reference
10.1145/3290605.3300468
10.1145/3290605.3300468 · External reference
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Perceptions of an AI-based clinical decision support tool for prescribing in multiple long-term conditions: a qualitative study of general practice clinicians in England
10.1136/bmjopen-2025-102833 · External reference
10.1145/3708359.3712136
10.1145/3708359.3712136 · External reference
To recommend or not to recommend: designing and evaluating AI-enabled decision support for time-critical medical events
10.1145/3757512 · External reference
Challenges for responsible AI design and workflow integration in healthcare: a case study of automatic feeding tube qualification in radiology
10.1145/3716500 · External reference
10.1145/3613904.3642343
10.1145/3613904.3642343 · External reference
User-centred design of a clinical decision support system for palliative care: insights from healthcare professionals
10.1177/20552076221150735 · External reference
Engaging clinicians early during the development of a graphical user display of an intelligent alerting system at the bedside
10.1016/j.ijmedinf.2021.104643 · External reference
A clinical decision support system for sleep staging tasks with explanations from artificial intelligence: user-centered design and evaluation study
10.2196/28659 · External reference
CarePre: an intelligent clinical decision assistance system
10.1145/3344258 · External reference
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User-centered development of explanation user interfaces for AI-based CDSS: lessons learned from early phases
10.3233/shti240478 · External reference
An explanation user interface for artificial intelligence-supported mechanical ventilation optimization for clinicians: user-centered design and formative usability study
10.2196/77481 · External reference
Evaluating the prototype of a clinical decision support system in primary care: qualitative study
10.2196/69875 · External reference
Application of a human-centered design for embedded machine learning model to develop data labeling software with nurses: Human-to-Artificial Intelligence (H2AI)
10.1016/j.ijmedinf.2023.105337 · External reference
Initial user-centred design of an AI-based clinical decision support system for primary care
10.3233/shti231125 · External reference
10.20944/preprints202506.2267.v1
10.20944/preprints202506.2267.v1 · External reference
Design of an interface to communicate artificial intelligence-based prognosis for patients with advanced solid tumors: a user-centered approach
10.1093/jamia/ocad201 · External reference
Co-design and evaluation of an intelligent decision support system for stroke rehabilitation assessment
10.1145/3415227 · External reference
Revealing ICU cognitive work through naturalistic decision-making methods
10.1177/1555343416664845 · External reference
10.1145/3290605.3300831
10.1145/3290605.3300831 · External reference
10.14236/ewic/bcshci2024.19
10.14236/ewic/bcshci2024.19 · External reference
Predictive analytics support for complex chronic medical conditions: an experience-based co-design study of physician managers’ needs and preferences
10.1016/j.ijmedinf.2024.105447 · External reference
10.1145/3746175.3746195
10.1145/3746175.3746195 · External reference
10.1145/3706598.3714272
10.1145/3706598.3714272 · External reference
10.1145/3643834.3660697
10.1145/3643834.3660697 · External reference
10.1145/3334480.3383061
10.1145/3334480.3383061 · External reference
An intelligent decision support system for acute postoperative endophthalmitis: design, development and evaluation of a smartphone application
10.1186/s12911-023-02214-3 · External reference
10.1145/3670653.3677483
10.1145/3670653.3677483 · External reference
Understanding and addressing challenges with electronic health record use in gynecological oncology: cross-sectional survey of multidisciplinary professionals in the United Kingdom and co-design of an integrated informatics platform to support clinical decision-making
10.2196/58657 · External reference
Evaluating the perceived utility of an artificial intelligence-powered clinical decision support system for depression treatment using a simulation center
10.1016/j.psychres.2021.114336 · External reference
10.1145/3617694.3623261
10.1145/3617694.3623261 · External reference
Why highly reliable decision support systems often lead to suboptimal performance and what we can do about it
10.1109/thms.2025.3584662 · External reference
A scoping review exploring the impact and negotiation of hierarchy in healthcare organisations
10.1111/nin.12571 · External reference
Clinician involvement in research on machine learning-based predictive clinical decision support for the hospital setting: a scoping review
10.1093/jamia/ocaa296 · External reference
Clinical decision-making among critical care nurses: a qualitative study
10.4236/health.2016.815173 · External reference
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10.1093/acprof:oso/9780198237907.001.0001
10.1093/acprof:oso/9780198237907.001.0001 · External reference
Epistemic injustice in healthcare: a philosophial analysis
10.1007/s11019-014-9560-2 · External reference
Compliance between registered nurses’ clinical judgment and documentation in homecare for older patients with COPD: a multiple case study
10.1177/20571585221149865 · External reference
Patient safety through nursing documentation: barriers identified by healthcare professionals and students
10.3389/fcomp.2021.624555 · External reference
Thinking like a nurse: a research-based model of clinical judgment in nursing
10.3928/01484834-20060601-04 · External reference
Decision-making model for nursing
10.1097/00005110-200312000-00003 · External reference
Research co-design in health: a rapid overview of reviews
10.1186/s12961-020-0528-9 · External reference
Unpacking the notion of participation in participatory design
10.1007/s10606-016-9259-4 · External reference
Consensus-based reporting guideline for participatory development and evaluation of digital health interventions
10.1038/s41746-026-02355-5 · External reference
A new framework for developing and evaluating complex interventions: update of Medical Research Council guidance
10.1136/bmj.n2061 · External reference
Building a system-based theory of change using participatory systems mapping
10.1177/1356389020980493 · External reference
Using theory of change to design and evaluate public health interventions: a systematic review
10.1186/s13012-016-0422-6 · External reference
Recognizing patient partner contributions to health research: a systematic review of reported practices
10.1186/s40900-023-00488-5 · External reference
Recognition, remuneration and reimbursement of patient and public involvement partners in pragmatic randomised controlled trials. a survey of author practices
10.1186/s40900-025-00796-y · External reference
The barriers and facilitators of radical innovation implementation in secondary healthcare: a systematic review
10.1108/jhom-12-2020-0493 · External reference
The updated consolidated framework for implementation research based on user feedback
10.1186/s13012-022-01245-0 · External reference
Beyond adoption: a new framework for theorizing and evaluating nonadoption, abandonment, and challenges to the scale-up, spread, and sustainability of health and care technologies
10.2196/jmir.8775 · External reference
Prospective real-world implementation of deep learning systems in healthcare: a systematic review guided by implementation science
10.1038/s41746-026-02358-2 · External reference
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Studying complexity in health services research: desperately seeking an overdue paradigm shift
10.1186/s12916-018-1089-4 · External reference
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Key points for an ethnography of AI: an approach towards crucial data
10.1057/s41599-024-02854-4 · External reference
10.7551/mitpress/9302.003.0002
10.7551/mitpress/9302.003.0002 · External reference
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Ethical, legal, and social considerations of AI-based medical decision-support tools: a scoping review
10.1016/j.ijmedinf.2022.104738 · External reference
10.1145/3551624.3555285
10.1145/3551624.3555285 · External reference
What hinders the uptake of computerized decision support systems in hospitals? A qualitative study and framework for implementation
10.1186/s13012-017-0644-2 · External reference
Artificial intelligence in healthcare: transforming the practice of medicine
10.7861/fhj.2021-0095 · External reference
Best practices in the reporting of participatory action research: embracing both the forest and the trees 1Ψ7
10.1177/0011000010376416 · External reference
TRIPOD+AI statement: updated guidance for reporting clinical prediction models that use regression or machine learning methods
10.1136/bmj-2023-078378 · External reference
