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Tag: clinician
Bibliography items where occurs: 81
- From Military to Healthcare: Adopting and Expanding Ethical Principles for Generative Artificial Intelligence / 2308.02448 / ISBN:https://doi.org/10.48550/arXiv.2308.02448 / Published by ArXiv / on (web) Publishing site
- Applications in Military Versus Healthcare
Identifying Ethical Concerns and Risks
GREAT PLEA Ethical Principles for Generative AI in Healthcare - The AI Revolution: Opportunities and Challenges for the Finance Sector / 2308.16538 / ISBN:https://doi.org/10.48550/arXiv.2308.16538 / Published by ArXiv / on (web) Publishing site
- 6 Regulation of AI and regulating through AI
- Ethical Framework for Harnessing the Power of AI in Healthcare and Beyond / 2309.00064 / ISBN:https://doi.org/10.48550/arXiv.2309.00064 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Black box and lack of transparency
3 Bias and fairness - FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging / 2109.09658 / ISBN:https://doi.org/10.48550/arXiv.2109.09658 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Fairness - For Equitable AI in Medical Imaging
3. Universality - For Standardised AI in Medical Imaging
4. Traceability - For Transparent and Dynamic AI in Medical Imaging
5. Usability - For Effective and Beneficial AI in Medical Imaging
6. Robustness - For Reliable AI in Medical Imaging
7. Explainability - For Enhanced Understanding of AI in Medical Imaging
9. Discussion and Conclusion - A Review of the Ethics of Artificial Intelligence and its Applications in the United States / 2310.05751 / ISBN:https://doi.org/10.48550/arXiv.2310.05751 / Published by ArXiv / on (web) Publishing site
- 2. Literature Review
- A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics / 2310.05694 / ISBN:https://doi.org/10.48550/arXiv.2310.05694 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. What LLMs can do for healthcare? from fundamental tasks to advanced applications
5. Improving fairness, accountability, transparency, and ethics
6. Discussion - Towards A Unified Utilitarian Ethics Framework for Healthcare Artificial Intelligence / 2309.14617 / ISBN:https://doi.org/10.48550/arXiv.2309.14617 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Utilitarian Ethics
Conclusion - Risk of AI in Healthcare: A Comprehensive Literature Review and Study Framework / 2309.14530 / ISBN:https://doi.org/10.48550/arXiv.2309.14530 / Published by ArXiv / on (web) Publishing site
- 3. Clinical Risks
4. Technical Risks - A Conceptual Algorithm for Applying Ethical Principles of AI to Medical Practice / 2304.11530 / ISBN:https://doi.org/10.48550/arXiv.2304.11530 / Published by ArXiv / on (web) Publishing site
- 2 Ethical concerns of AI in medicine
3 Ethical datasets and algorithm development guidelines
4 Towards solving key ethical challenges in Medical AI
5 Ethical guidelines for medical AI model deployment
6 Discussion - FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare / 2309.12325 / ISBN:https://doi.org/10.48550/arXiv.2309.12325 / Published by ArXiv / on (web) Publishing site
- Abstract
INTRODUCTION
METHODS
FUTURE-AI GUIDELINE - RAISE -- Radiology AI Safety, an End-to-end lifecycle approach / 2311.14570 / ISBN:https://doi.org/10.48550/arXiv.2311.14570 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
3. Production deployment monitoring phase
4. Post-market surveillance phase - Designing Guiding Principles for NLP for Healthcare: A Case Study of Maternal Health / 2312.11803 / ISBN:https://doi.org/10.48550/arXiv.2312.11803 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Objective
3 Materials and methods
4 Results
6 Conclusion - Autonomous Threat Hunting: A Future Paradigm for AI-Driven Threat Intelligence / 2401.00286 / ISBN:https://doi.org/10.48550/arXiv.2401.00286 / Published by ArXiv / on (web) Publishing site
- 7. Evaluation metrics and performance benchmarks
- Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review / 2401.01519 / ISBN:https://doi.org/10.48550/arXiv.2401.01519 / Published by ArXiv / on (web) Publishing site
- 3. LLMs in clinical and counseling psychology
7. Challenges and future directions - AI Ethics Principles in Practice: Perspectives of Designers and Developers / 2112.07467 / ISBN:https://doi.org/10.48550/arXiv.2112.07467 / Published by ArXiv / on (web) Publishing site
- IV. Results
- Unmasking Bias in AI: A Systematic Review of Bias Detection and Mitigation Strategies in Electronic Health Record-based Models / 2310.19917 / ISBN:https://doi.org/10.48550/arXiv.2310.19917 / Published by ArXiv / on (web) Publishing site
- Results
- Generative Artificial Intelligence in Healthcare: Ethical Considerations and Assessment Checklist / 2311.02107 / ISBN:https://doi.org/10.48550/arXiv.2311.02107 / Published by ArXiv / on (web) Publishing site
- Conclusion
- A Survey on Human-AI Teaming with Large Pre-Trained Models / 2403.04931 / ISBN:https://doi.org/10.48550/arXiv.2403.04931 / Published by ArXiv / on (web) Publishing site
- 3 Effective Human-AI Joint Systems
- Responsible Artificial Intelligence: A Structured Literature Review / 2403.06910 / ISBN:https://doi.org/10.48550/arXiv.2403.06910 / Published by ArXiv / on (web) Publishing site
- 3. Analysis
- Trust in AI: Progress, Challenges, and Future Directions / 2403.14680 / ISBN:https://doi.org/10.48550/arXiv.2403.14680 / Published by ArXiv / on (web) Publishing site
- 3. Findings
- Beyond Personhood: Agency, Accountability, and the Limits of Anthropomorphic Ethical Analysis / 2404.13861 / ISBN:https://doi.org/10.48550/arXiv.2404.13861 / Published by ArXiv / on (web) Publishing site
- 4 Alternatives to AI as Agent
- AI Procurement Checklists: Revisiting Implementation in the Age of AI Governance / 2404.14660 / ISBN:https://doi.org/10.48550/arXiv.2404.14660 / Published by ArXiv / on (web) Publishing site
- 1 Technical assessments require an AI expert to complete —
and we don’t have enough experts
- A Survey on Large Language Models for Critical Societal Domains: Finance, Healthcare, and Law / 2405.01769 / ISBN:https://doi.org/10.48550/arXiv.2405.01769 / Published by ArXiv / on (web) Publishing site
- 4 Medicine and Healthcare
- A scoping review of using Large Language Models (LLMs) to investigate Electronic Health Records (EHRs) / 2405.03066 / ISBN:https://doi.org/10.48550/arXiv.2405.03066 / Published by ArXiv / on (web) Publishing site
- 2 Materials
3 Results
4 Discussion - Towards Clinical AI Fairness: Filling Gaps in the Puzzle / 2405.17921 / ISBN:https://doi.org/10.48550/arXiv.2405.17921 / Published by ArXiv / on (web) Publishing site
- Results
Methods in clinical AI fairness research
Discussion
Additional material - Promoting Fairness and Diversity in Speech Datasets for Mental Health and Neurological Disorders Research / 2406.04116 / ISBN:https://doi.org/10.48550/arXiv.2406.04116 / Published by ArXiv / on (web) Publishing site
- 3. Related Work
4. Desiderata
5. Methodology
6. Discussion
Appendix A. Terminology - Fair by design: A sociotechnical approach to justifying the fairness of AI-enabled systems across the lifecycle / 2406.09029 / ISBN:https://doi.org/10.48550/arXiv.2406.09029 / Published by ArXiv / on (web) Publishing site
- Abstract
2 Fairness and AI
3 Assuring fairness across the AI lifecycle
4 Assuring AI fairness in healthcare
5 Conclusion - Applications of Generative AI in Healthcare: algorithmic, ethical, legal and societal considerations / 2406.10632 / ISBN:https://doi.org/10.48550/arXiv.2406.10632 / Published by ArXiv / on (web) Publishing site
- III. Analysis
Aappendix A Societal aspects - Justice in Healthcare Artificial Intelligence in Africa / 2406.10653 / ISBN:https://doi.org/10.48550/arXiv.2406.10653 / Published by ArXiv / on (web) Publishing site
- 1. Beyond Bias and Fairness
7. Addressing Bias and Enforcing Fairness - Leveraging Large Language Models for Patient Engagement: The Power of Conversational AI in Digital Health
/ 2406.13659 / ISBN:https://doi.org/10.48550/arXiv.2406.13659 / Published by ArXiv / on (web) Publishing site
- III. CASE STUDIES : APPLICATIONS OF LLM S IN PATIENT
ENGAGEMENT
- Operationalising AI governance through ethics-based auditing: An industry case study / 2407.06232 / Published by ArXiv / on (web) Publishing site
- 2. The need to operationalise AI governance
- FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare / 2309.12325 / ISBN:https://doi.org/10.48550/arXiv.2309.12325 / Published by ArXiv / on (web) Publishing site
- Table 1
Table 2 - Past, Present, and Future: A Survey of The Evolution of Affective Robotics For Well-being / 2407.02957 / ISBN:https://doi.org/10.48550/arXiv.2407.02957 / Published by ArXiv / on (web) Publishing site
- Abstract
III. Method
IV. Evolution of Affective Robots for Well-Being
VI. Future Opportunities in Affective Robotivs for Well-Being - Visualization Atlases: Explaining and Exploring Complex Topics through Data, Visualization, and Narration / 2408.07483 / ISBN:https://doi.org/10.48550/arXiv.2408.07483 / Published by ArXiv / on (web) Publishing site
- 4 Interviews with Visualization Atlas Creators
- Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Survey / 2408.12880 / ISBN:https://doi.org/10.48550/arXiv.2408.12880 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 Multimodal Medical Studies
Appendix - Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systems / 2408.15550 / ISBN:https://doi.org/10.48550/arXiv.2408.15550 / Published by ArXiv / on (web) Publishing site
- 5 Trustworthy and Responsible AI in
Human-centric Applications
- Data-Centric Foundation Models in Computational Healthcare: A Survey / 2401.02458 / ISBN:https://doi.org/10.48550/arXiv.2401.02458 / Published by ArXiv / on (web) Publishing site
- A Healthcare Data Modalities
- Navigating LLM Ethics: Advancements, Challenges, and Future Directions / 2406.18841 / ISBN:https://doi.org/10.48550/arXiv.2406.18841 / Published by ArXiv / on (web) Publishing site
- IV. Findings and Resultant Themes
- Safety challenges of AI in medicine / 2409.18968 / ISBN:https://doi.org/10.48550/arXiv.2409.18968 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
2 Inherent problems of AI related to medicine
4 AI safety issues related to large language models in medicine - Clinnova Federated Learning Proof of Concept: Key Takeaways from a Cross-border Collaboration / 2410.02443 / ISBN:https://doi.org/10.48550/arXiv.2410.02443 / Published by ArXiv / on (web) Publishing site
- V. Proof of Concepts 2
- Distribution of Responsibility During the Usage of AI-Based Exoskeletons for Upper Limb Rehabilitation / 2410.16887 / ISBN:https://doi.org/10.48550/arXiv.2410.16887 / Published by ArXiv / on (web) Publishing site
- IV. Different Factors Improved by Adopting AI-Based Exoskeleton
- Trustworthy XAI and Application / 2410.17139 / ISBN:https://doi.org/10.48550/arXiv.2410.17139 / Published by ArXiv / on (web) Publishing site
- 3 Applications of XAI
- Demystifying Large Language Models for Medicine: A Primer / 2410.18856 / ISBN:https://doi.org/10.48550/arXiv.2410.18856 / Published by ArXiv / on (web) Publishing site
- Prompt engineering
- A Comprehensive Review of Multimodal XR Applications, Risks, and Ethical Challenges in the Metaverse / 2411.04508 / ISBN:https://doi.org/10.48550/arXiv.2411.04508 / Published by ArXiv / on (web) Publishing site
- 3. XR Applications: Expanding Multimodal Interactions Across Domains
- A Survey on Medical Large Language Models: Technology, Application, Trustworthiness, and Future Directions / 2406.03712 / ISBN:https://doi.org/10.48550/arXiv.2406.03712 / Published by ArXiv / on (web) Publishing site
- Abstract
I. Introduction
IV. Improving Algorithms for Med-LLMs
V. Applying Medical LLMs
VI. Trustworthiness and Safety - Nteasee: A mixed methods study of expert and general population perspectives on deploying AI for health in African countries / 2409.12197 / ISBN:https://doi.org/10.48550/arXiv.2409.12197 / Published by ArXiv / on (web) Publishing site
- 4 Results
- Framework for developing and evaluating ethical collaboration between expert and machine / 2411.10983 / ISBN:https://doi.org/10.48550/arXiv.2411.10983 / Published by ArXiv / on (web) Publishing site
- Abstract
1. Introduction
2. Method - Ethical Challenges and Evolving Strategies in the Integration of Artificial Intelligence into Clinical Practice / 2412.03576 / ISBN:https://doi.org/10.48550/arXiv.2412.03576 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction and Motivation
Core Ethical Challenges - From Principles to Practice: A Deep Dive into AI Ethics and Regulations / 2412.04683 / ISBN:https://doi.org/10.48550/arXiv.2412.04683 / Published by ArXiv / on (web) Publishing site
- II AI Practice and Contextual Integrity
- Technology as uncharted territory: Contextual integrity and the notion of AI as new ethical ground / 2412.05130 / ISBN:https://doi.org/10.48550/arXiv.2412.05130 / Published by ArXiv / on (web) Publishing site
- II AI Practice and Contextual Integrity
- Ethical Challenges and Evolving Strategies in the Integration of Artificial Intelligence into Clinical Practice / 2412.03576 / ISBN:https://doi.org/10.48550/arXiv.2412.03576 / Published by ArXiv / on (web) Publishing site
- Discussion
- Datasheets for Healthcare AI: A Framework for Transparency and Bias Mitigation / 2501.05617 / ISBN:https://doi.org/10.48550/arXiv.2501.05617 / Published by ArXiv / on (web) Publishing site
- 2. Literature Review
- Addressing Intersectionality, Explainability, and Ethics in AI-Driven Diagnostics: A Rebuttal and Call for Transdiciplinary Action / 2501.08497 / ISBN:https://doi.org/10.48550/arXiv.2501.08497 / Published by ArXiv / on (web) Publishing site
- 6 Recommendations for an Inclusive and Ethical Framework
- Towards Safe AI Clinicians: A Comprehensive Study on Large Language Model Jailbreaking in Healthcare / 2501.18632 / ISBN:https://doi.org/10.48550/arXiv.2501.18632 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
Model Guardrail Enhancemen
Limitations and Future Work - The Human-AI Handshake Framework: A Bidirectional Approach to Human-AI Collaboration / 2502.01493 / ISBN:https://doi.org/10.48550/arXiv.2502.01493 / Published by ArXiv / on (web) Publishing site
- Literature Review
- Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription / 2502.04356 / ISBN:https://doi.org/10.48550/arXiv.2502.04356 / Published by ArXiv / on (web) Publishing site
- Abstract
II. Background
III. State-of-the-Art in Open Healthcare LLMs and AIFMs
IV. Leveraging Open LLMs for Prescription: A Case Study - Integrating Generative Artificial Intelligence in ADRD: A Framework for Streamlining Diagnosis and Care in Neurodegenerative Diseases
/ 2502.06842 / ISBN:https://doi.org/10.48550/arXiv.2502.06842 / Published by ArXiv / on (web) Publishing site
- Abstract
Introduction
High Quality Data Collection
Conclusion - From large language models to multimodal AI: A scoping review on the potential of generative AI in medicine
/ 2502.09242 / ISBN:https://doi.org/10.48550/arXiv.2502.09242 / Published by ArXiv / on (web) Publishing site
- 5 Multimodal language models in medicine
7 Discussion - Relational Norms for Human-AI Cooperation / 2502.12102 / ISBN:https://doi.org/10.48550/arXiv.2502.12102 / Published by ArXiv / on (web) Publishing site
- Section 2: Distinctive Characteristics of AI and Implications for Relational Norms
- On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective / 2502.14296 / ISBN:https://doi.org/10.48550/arXiv.2502.14296 / Published by ArXiv / on (web) Publishing site
- 9 Trustworthiness in Downstream Applications
10 Further Discussion - Surgical Scene Understanding in the Era of Foundation AI Models: A Comprehensive Review / 2502.14886 / ISBN:https://doi.org/10.48550/arXiv.2502.14886 / Published by ArXiv / on (web) Publishing site
- I. Introduction
II. Background and Challenges
IV. ML/DL Applications in Surgical Workflow Analysis
VI. Open Issues and Future Research Directions in Surgical Scene Understanding - Fair Foundation Models for Medical Image Analysis: Challenges and Perspectives / 2502.16841 / ISBN:https://doi.org/10.48550/arXiv.2502.16841 / Published by ArXiv / on (web) Publishing site
- 3 Data Documentation
- Evaluating Large Language Models on the Spanish Medical Intern Resident (MIR) Examination 2024/2025:A Comparative Analysis of Clinical Reasoning and Knowledge Application / 2503.00025 / ISBN:https://doi.org/10.48550/arXiv.2503.00025 / Published by ArXiv / on (web) Publishing site
- 5. Conclusion
- Can AI Model the Complexities of Human Moral Decision-Making? A Qualitative Study of Kidney Allocation Decisions / 2503.00940 / ISBN:https://doi.org/10.48550/arXiv.2503.00940 / Published by ArXiv / on (web) Publishing site
- 3 Methodology
- Vision Language Models in Medicine / 2503.01863 / ISBN:https://doi.org/10.48550/arXiv.2503.01863 / Published by ArXiv / on (web) Publishing site
- I. Introduction
III. Core Concepts of Visual Language Modeling
V. Challenges and Limitations
VI. Opportunities and Future Directions - Medical Hallucinations in Foundation Models and Their Impact on Healthcare / 2503.05777 / ISBN:https://doi.org/10.48550/arXiv.2503.05777 / Published by ArXiv / on (web) Publishing site
- Abstract
1 Introduction
2 LLM Hallucinations in Medicine
3 Causes of Hallucinations
4 Detection and Evaluation of Medical Hallucinations
5 Mitigation Strategies
8 Survey on AI/LLM Adoption and Medical Hallucinations Among Healthcare Professionals and Researchers
9 Regulatory and Legal Considerations for AI Hallucinations in Healthcare
10 Conclusion - Decoding the Black Box: Integrating Moral Imagination with Technical AI Governance / 2503.06411 / ISBN:https://doi.org/10.48550/arXiv.2503.06411 / Published by ArXiv / on (web) Publishing site
- 6 Case Studies and Domain Applications
- Detecting Dataset Bias in Medical AI: A Generalized and Modality-Agnostic Auditing Framework / 2503.09969 / ISBN:https://doi.org/10.48550/arXiv.2503.09969 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
3 Discussion
4 Methods - LLMs in Disease Diagnosis: A Comparative Study of DeepSeek-R1 and O3 Mini Across Chronic Health Conditions
/ 2503.10486 / ISBN:https://doi.org/10.48550/arXiv.2503.10486 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
5 Discussion
6 Conclusion - Ethical Implications of AI in Data Collection: Balancing Innovation with Privacy / 2503.14539 / ISBN:https://doi.org/10.48550/arXiv.2503.14539 / Published by ArXiv / on (web) Publishing site
- Introduction
- Leveraging LLMs for User Stories in AI Systems: UStAI Dataset / 2504.00513 / ISBN:https://doi.org/10.48550/arXiv.2504.00513 / Published by ArXiv / on (web) Publishing site
- 5 Discussion
- Ethical AI on the Waitlist: Group Fairness Evaluation of LLM-Aided Organ Allocation / 2504.03716 / ISBN:https://doi.org/10.48550/arXiv.2504.03716 / Published by ArXiv / on (web) Publishing site
- 1 Introduction
5 Related Works - AI-Driven Healthcare: A Review on Ensuring Fairness and Mitigating Bias / 2407.19655 / ISBN:https://doi.org/10.48550/arXiv.2407.19655 / Published by ArXiv / on (web) Publishing site
- 1 Applications of AI in Healthcare
4 Research gaps and Future directions
5 Conclusion - >Publishing site
- Case Studies
- A Design Framework for operationalizing Trustworthy Artificial Intelligence in Healthcare: Requirements, Tradeoffs and Challenges for its Clinical Adoption / 2504.19179 / ISBN:https://doi.org/10.48550/arXiv.2504.19179 / Published by ArXiv / on (web) Publishing site
- 1. Introduction
2. Fundamentals of Trustworthy AI
3. An overview of the AI ecosystem in the medical field: processes, data, and stakeholders
4. Design framework for medical AI systems
5. Tradeoffs between TAI principles and requirements
6. Challenges towards the practical adoption of the design framework in healthcare
7. Conclusions and outlook - Federated learning, ethics, and the double black box problem in medical AI
/ 2504.20656 / ISBN:https://doi.org/10.48550/arXiv.2504.20656 / Published by ArXiv / on (web) Publishing site
- 6 Further ethical concerns
- Ethical AI in the Healthcare Sector: Investigating Key Drivers of Adoption through the Multi-Dimensional Ethical AI Adoption Model (MEAAM) / 2505.02062 / ISBN:https://doi.org/10.9734/ajmah/2025/v23i51228 / Published by ArXiv / on (web) Publishing site
- 2. Literature Review and Theoretical Mechanism
3. Research Methods
6. Future Research - Formalising Human-in-the-Loop: Computational Reductions, Failure Modes, and Legal-Moral Responsibility / 2505.10426 / ISBN:https://doi.org/10.48550/arXiv.2505.10426 / Published by ArXiv / on (web) Publishing site
- Introduction
- Opacity as a Feature, Not a Flaw: The LoBOX Governance Ethic for Role-Sensitive Explainability and Institutional Trust in AI
/ 2505.20304 / ISBN:https://doi.org/10.48550/arXiv.2505.20304 / Published by ArXiv / on (web) Publishing site
- 4 Application scenarios
- Making Sense of the Unsensible: Reflection, Survey, and Challenges for XAI in Large Language Models Toward Human-Centered AI / 2505.20305 / ISBN:https://doi.org/10.48550/arXiv.2505.20305 / Published by ArXiv / on (web) Publishing site
- 3 What Is XAI in the Context of LLMs?
5 Audience-Centered XAI role in LLMs - Simulating Ethics: Using LLM Debate Panels to Model Deliberation on Medical Dilemmas / 2505.21112 / ISBN:https://doi.org/10.48550/arXiv.2505.21112 / Published by ArXiv / on (web) Publishing site
- 4. Results
6. Future Directions - DeepSeek in Healthcare: A Survey of Capabilities, Risks, and Clinical Applications of Open-Source Large Language Models / 2506.01257 / ISBN:https://doi.org/10.48550/arXiv.2506.01257 / Published by ArXiv / on (web) Publishing site
- Clinical Applications
Future Directions
Discussion - Surgeons Awareness, Expectations, and Involvement with Artificial Intelligence: a Survey Pre and Post the GPT Era / 2506.08258 / ISBN:https://doi.org/10.48550/arXiv.2506.08258 / Published by ArXiv / on (web) Publishing site
- 3. Results
5. Conclusions