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Tag: kidney
Bibliography items where occurs: 23
- The AI Index 2022 Annual Report / 2205.03468 / ISBN:https://doi.org/10.48550/arXiv.2205.03468 / Published by ArXiv / on (web) Publishing site
- Chapter 2 Technical Performance
- Deepfakes, Phrenology, Surveillance, and More! A Taxonomy of AI Privacy Risks / 2310.07879 / ISBN:https://doi.org/10.48550/arXiv.2310.07879 / Published by ArXiv / on (web) Publishing site
- 4 Taxonomy of AI Privacy Risks
- 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
- References
- Human participants in AI research: Ethics and transparency in practice / 2311.01254 / ISBN:https://doi.org/10.48550/arXiv.2311.01254 / Published by ArXiv / on (web) Publishing site
- References
- The METRIC-framework for assessing data quality for trustworthy AI in medicine: a systematic review / 2402.13635 / ISBN:https://doi.org/10.48550/arXiv.2402.13635 / Published by ArXiv / on (web) Publishing site
- METRIC-framework for medical training data
- The Pursuit of Fairness in Artificial Intelligence Models A Survey / 2403.17333 / ISBN:https://doi.org/10.48550/arXiv.2403.17333 / Published by ArXiv / on (web) Publishing site
- 4 Practical cases of unfairness in real-world setting
- Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback / 2404.10271 / ISBN:https://doi.org/10.48550/arXiv.2404.10271 / Published by ArXiv / on (web) Publishing site
- 8. How Should We Account for Behavioral
Aspects and Human Cognitive Structures?
References - 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
- 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
- 3 Assuring fairness across the AI lifecycle
- Challenges and Best Practices in Corporate AI Governance:Lessons from the Biopharmaceutical Industry / 2407.05339 / ISBN:https://doi.org/10.48550/arXiv.2407.05339 / Published by ArXiv / on (web) Publishing site
- 3 Practical implementation challenges | What to be prepared for?
- Operationalising AI governance through ethics-based auditing: An industry case study / 2407.06232 / Published by ArXiv / on (web) Publishing site
- 6. Lessons learned from AstraZeneca’s 2021 AI audit
- Why should we ever automate moral decision making? / 2407.07671 / ISBN:https://doi.org/10.48550/arXiv.2407.07671 / Published by ArXiv / on (web) Publishing site
- 2 Reasons for automated moral decision making
References - 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:
- 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
- References
- Beyond Algorithmic Fairness: A Guide to Develop and Deploy Ethical AI-Enabled Decision-Support Tools / 2409.11489 / ISBN:https://doi.org/10.48550/arXiv.2409.11489 / 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
- References
- Democratizing Reward Design for Personal and Representative Value-Alignment / 2410.22203 / ISBN:https://doi.org/10.48550/arXiv.2410.22203 / Published by ArXiv / on (web) Publishing site
- References
- The doctor will polygraph you now: ethical concerns with AI for fact-checking patients / 2408.07896 / ISBN:https://doi.org/10.48550/arXiv.2408.07896 / Published by ArXiv / on (web) Publishing site
- 2. Clinical, Technical, and Ethical Concerns
References: - Collaborative Participatory Research with LLM Agents in South Asia: An Empirically-Grounded Methodological Initiative and Agenda from Field Evidence in Sri Lanka / 2411.08294 / ISBN:https://doi.org/10.48550/arXiv.2411.08294 / 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
- Cases and Examples
- 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
- Abstract
1 Introduction
2 Related Work
3 Methodology
4 Main Findings and Themes
5 Discussion
References
Appendices - 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
- Appendices
- 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
- Abstract
1 Introduction
2 Methods
3 Results
4 Conclusion
5 Related Works
References
Appendix