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Artificial intelligence (AI) has become commonplace in our everyday lives and in healthcare. Peritoneal dialysis (PD) is a cost-effective method of treatment for kidney failure that is preferred by many patients, but its uptake is limited by several barriers. With the rapid advancements in AI, researchers are developing new tools that could mitigate some of these barriers to promote uptake and improve patient outcomes. AI has the capacity to assist with patient selection and management, predict patient technique failure, predict patient outcomes, and improve accessibility of patient education. Patients already have access to some open-source AI tools, and others are being rapidly developed for implementation in the dialysis space. For ethical implementation, it is essential for providers to understand the advantages and limitations of AI-based approaches and be able to interpret the common metrics used to evaluate their performance. In this review, we provide a general overview of AI with information necessary for clinicians to critically evaluate AI models and tools. We then review existing AI models and tools for PD.
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Hailey Yetman
Icahn School of Medicine at Mount Sinai
Lili Chan
Icahn School of Medicine at Mount Sinai
Kidney and Dialysis
Icahn School of Medicine at Mount Sinai
Murphy Oil Corporation (United States)
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Yetman et al. (Wed,) studied this question.
synapsesocial.com/papers/6a158f005347fbb1739ff681 — DOI: https://doi.org/10.3390/kidneydial5020020
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