Empowering inclusivity: improving readability of living kidney donation information with ChatGPT

Background: Large Language Models (LLMs) are emerging as promising tools in healthcare. This systematic review examines LLMs' potential applications in nephrology, highlighting their benefits and limitations. Methods: We conducted a literature search in PubMed and Web of Science, selecting studies based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The review focuses on the latest advancements of LLMs in nephrology from 2020 to 2024. PROSPERO registration number: CRD42024550169. Results: Fourteen studies met the inclusion criteria and were categorized into five key areas of nephrology: Streamlining workflow, disease prediction and prognosis, laboratory data interpretation and management, renal dietary management, and patient education. LLMs showed high performance in various clinical tasks, including managing continuous renal replacement therapy (CRRT) alarms (GPT-4 accuracy 90-94%) for reducing intensive care unit (ICU) alarm fatigue, and predicting chronic kidney diseases (CKD) progression (improved positive predictive value from 6.7% to 20.9%). In patient education, GPT-4 excelled at simplifying medical information by reducing readability complexity, and accurately translating kidney transplant resources. Gemini provided the most accurate responses to frequently asked questions (FAQs) about CKD. Conclusions: While the incorporation of LLMs in nephrology shows promise across various levels of patient care, their broad implementation is still premature. Further research is required to validate these tools in terms of accuracy, rare and critical conditions, and real-world performance.

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Generative AI in Critical Care Nephrology: Applications and Future Prospects

Cheungpasitporn,

Thongprayoon,

Ronco

et al. 2024

Blood Purif

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Background: Generative artificial intelligence (AI) is rapidly transforming various aspects of healthcare, including critical care nephrology. Large language models (LLMs), a key technology in generative AI, show promise in enhancing patient care, streamlining workflows, and advancing research in this field. Summary: This review analyzes the current applications and future prospects of generative AI in critical care nephrology. Recent studies demonstrate the capabilities of LLMs in diagnostic accuracy, clinical reasoning, and continuous renal replacement therapy (CRRT) alarm troubleshooting. As we enter an era of multiagent models and automation, the integration of generative AI into critical care nephrology holds promise for improving patient care, optimizing clinical processes, and accelerating research. However, careful consideration of ethical implications and continued refinement of these technologies are essential for their responsible implementation in clinical practice. This review explores the current and potential applications of generative AI in nephrology, focusing on clinical decision support, patient education, research, and medical education. Additionally, we examine the challenges and limitations of AI implementation, such as privacy concerns, potential bias, and the necessity for human oversight. Key Messages: (i) LLMs have shown potential in enhancing diagnostic accuracy, clinical reasoning, and CRRT alarm troubleshooting in critical care nephrology. (ii) Generative AI offers promising applications in patient education, literature review, and academic writing within the field of nephrology. (iii) The integration of AI into electronic health records and clinical workflows presents both opportunities and challenges for improving patient care and research. (iv) Addressing ethical concerns, ensuring data privacy, and maintaining human oversight are crucial for the responsible implementation of AI in critical care nephrology.

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Empowering inclusivity: improving readability of living kidney donation information with ChatGPT

Cited by 6 publications

References 31 publications

Exploring the ability of ChatGPT to create quality patient education resources about kidney transplant

Exploring the ability of ChatGPT to create quality patient education resources about kidney transplant

Clinical Applications and Limitations of Large Language Models in Nephrology: A Systematic Review

Generative AI in Critical Care Nephrology: Applications and Future Prospects

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