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Machine Learning to Assist in Managing Acute Kidney Injury in General Wards: Multicenter Retrospective Study

Machine Learning to Assist in Managing Acute Kidney Injury in General Wards: Multicenter Retrospective Study

This inconsistency in defining AKI, especially in terms of baseline serum creatinine (SCr) and recovery criteria for AKD, leads to ambiguity in labeling and makes it difficult to compare the performance of different AI models across studies [13,14]. The variability in baseline SCr determination further complicates the issue [14-16].

Nam-Jun Cho, Inyong Jeong, Se-Jin Ahn, Hyo-Wook Gil, Yeongmin Kim, Jin-Hyun Park, Sanghee Kang, Hwamin Lee

J Med Internet Res 2025;27:e66568

Self-Monitoring Kidney Function Post Transplantation: Reliability of Patient-Reported Data

Self-Monitoring Kidney Function Post Transplantation: Reliability of Patient-Reported Data

To the best of our knowledge, no studies have assessed the reliability and accuracy of patient-generated creatinine data or looked at the level of adherence to a protocol of self-monitoring creatinine. This is unfortunate, as the introduction of self-monitoring offers a good opportunity to improve post-transplantation care. Our first research goal was to investigate the level of adherence of kidney transplant patients to a creatinine monitoring schedule.

Céline van Lint, Wenxin Wang, Sandra van Dijk, Willem-Paul Brinkman, Ton JM Rövekamp, Mark A Neerincx, Ton J Rabelink, Paul JM van der Boog

J Med Internet Res 2017;19(9):e316