Why_this_webapp Bibliography

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
References

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
References

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
References

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

Fairness And Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, And Mitigation Strategies / 2304.07683 / ISBN:https://doi.org/10.48550/arXiv.2304.07683 / Published by ArXiv / on (web) Publishing site

References

Responsible AI Considerations in Text Summarization Research: A Review of Current Practices / 2311.11103 / ISBN:https://doi.org/10.48550/arXiv.2311.11103 / Published by ArXiv / on (web) Publishing site

References

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
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

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
References

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

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
References

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
Reference

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

3 Results
4 Discussion
References

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
References

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
References

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

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

REFERENCES:
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

ValueCompass: A Framework of Fundamental Values for Human-AI Alignment / 2409.09586 / ISBN:https://doi.org/10.48550/arXiv.2409.09586 / Published by ArXiv / on (web) Publishing site

References

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

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 Trustworthy 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
References

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

2 Methods
3 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

Responsible AI Governance: A Response to UN Interim Report on Governing AI for Humanity / 2412.12108 / ISBN:https://doi.org/10.48550/arXiv.2412.12108 / Published by ArXiv / on (web) Publishing site

References

Implications of Artificial Intelligence on Health Data Privacy and Confidentiality / 2501.01639 / ISBN:https://doi.org/10.48550/arXiv.2501.01639 / Published by ArXiv / on (web) Publishing site

References

Trust and Dependability in Blockchain & AI Based MedIoT Applications: Research Challenges and Future Directions / 2501.02647 / ISBN:https://doi.org/10.48550/arXiv.2501.02647 / Published by ArXiv / on (web) Publishing site

References

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. / 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. / 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. / Published by ArXiv / on (web) Publishing site

Literature Review
References

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription / 2502.04356 / ISBN:https://doi.org/10.48550/arXiv. / Published by ArXiv / on (web) Publishing site

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. / 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

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
References

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

Why do we do this?: Moral Stress and the Affective Experience of Ethics in Practice / 2502.18395 / ISBN:https://doi.org/10.48550/arXiv.2502.18395 / Published by ArXiv / on (web) Publishing site

References

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
References

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

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

Advancing Human-Machine Teaming: Concepts, Challenges, and Applications / 2503.16518 / ISBN:https://doi.org/10.48550/arXiv.2503.16518 / Published by ArXiv / on (web) Publishing site

References

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