PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 14, 2025Kidney and Dialysis3 citationsOpen Access

Artificial Intelligence and Its Future Impact on Peritoneal Dialysis

HYHailey YetmanLCLili Chan

Key Points

Key points are not available for this paper at this time.

Abstract

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.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Yetman et al. (2025) studied this question.

synapsesocial.com/papers/6a158f005347fbb1739ff681https://doi.org/10.3390/kidneydial5020020
Ask AI
Helpful
Bookmark
Share
View Full Paper

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Factors related to patient selection and initiation of peritoneal dialysis2017 · 3 citations
  2. 2Prevention Of Peritoneal Dialysis–Related Infections2011 · 30 citations
  3. 3Integrating Retrieval-Augmented Generation with Large Language Models in Nephrology: Advancing Practical Applications2024 · 165 citations
  4. 4Association between causes of peritoneal dialysis technique failure and all-cause mortality2018 · 52 citations
  5. 5Machine-learning algorithms define pathogen-specific local immune fingerprints in peritoneal dialysis patients with bacterial infections2017 · 84 citations