Back
For best output, select "Paper Size" as "A4" and "Margin" as "0" or "None".
To save or print to PDF, please select Print Destination > Save as PDF, enable Background Graphics under "More Settings", then click "Save".
During the congress, E-Posters will be accessible to all participants on the congress website 24/7, as well as in the E-poster stations in the congress center.
Preparing your E-Poster
Please review the E-Poster format requirements carefully when preparing your E-Poster. Should your E-Poster not meet the mentioned requirements, it may not be displayed as described above.
E-Poster Submission Deadline
Please prepare and upload your E-Poster no later than March 14, 2026 11.59PM CET. After this date, you will no longer be able to prepare and upload your E-poster and it will not be displayed and accessible on the congress website.
Please follow the instructions below to input your abstract title.
Abstract titles should be brief and reflect the content of the abstract.
The growing implementation of artificial intelligence (AI) in nephrology presents unique ethical challenges due to the chronic nature of kidney diseases, patient vulnerability, and critical decisions regarding renal replacement therapy (RRT). Despite AI’s potential benefits for diagnosis, prognosis, and treatment optimization, there remains a significant gap between technological development and specialty‑specific ethical frameworks. This study aims to develop a comprehensive ethical‑regulatory framework for the responsible implementation of AI in nephrology practice, addressing issues of privacy, transparency, accountability, and equity.
The methodology was grounded in the ethical principles of Beauchamp and Childress (autonomy, beneficence, non‑maleficence, and justice) as the analytical framework. We conducted a detailed comparative analysis of international regulations, including the FDA (United States), the Medical Device Regulation and the AI Act (European Union), and ANVISA regulations in Brazil. We analyzed specific cases of AI implementation in nephrology, including systems for predicting CKD progression, optimization of transplant waitlists, and home monitoring. Through an iterative process, we developed practical tools: ethical compliance checklists for developers, institutions, and regulators; AI‑specific informed consent templates; and quantitative metrics for ethical auditing.
We identified four critical ethical domains: (1) Privacy — the need to protect extensive longitudinal data and employ k‑anonymity techniques; (2) Transparency — implementing explainability at three levels (global, local, and counterfactual) using methods such as SHAP and LIME; (3) Accountability — establishing a clear chain of accountability from developers to clinicians; (4) Equity — fairness metrics including demographic parity and equalized odds. We developed an institutional governance framework featuring technical, clinical, and patient committees. We proposed specific metrics for quarterly, semiannual, and annual ethical audits. The regulatory analysis revealed significant normative gaps, especially in Brazil, where the AI Legal Framework is still under consideration.
This work presents the first comprehensive ethical framework specific to AI in nephrology, offering practical tools for responsible implementation. Key recommendations include establishing AI ethics committees within institutions, developing specialty‑specific guidelines by the nephrology community, harmonizing international regulations, and providing continuing education on ethical AI. The proposed framework can serve as a model for other medical specialties and contribute to the responsible development of AI in healthcare, ensuring that technological benefits are distributed equitably while preserving patient autonomy and professional accountability.
