Acute Kidney Injury (AKINow) Artificial Intelligence (AI)

Welcome to the AKINow AI Workgroup Page.

Our goal is to help clinicians, patients and researchers use AI to improve the quality, accessibility, affordability and equity of care. Email us at AI Workgroup via

Dr. Jay Koyner introduces AKINow, the Recognition and Intervention Workgroup, and explains their focus on Artificial Intelligence.

  AKINow AI Spotlight

Artificial Machine Learning and Data Science: Demystifying the Hype

screenshot from Youtube video.

Is AI new to you? Listen to Dr. Nadkarni provide an overview of artificial machine learning and data science for the novice learner. If you have any questions or need additional information, please email us at

5 Myths about AI in AKI

5 Myths about AI in AKI.

AI is new to many clinicians and often there are a lot of misunderstandings, favorable or unfavorable, about AI and the research within it. Listen to Dr. Singh’s quick snapshot of the 5 myths of AI in AKI.

Recorded November 2021

AKI Detection: AKI Sniffers

AKI Sniffers video presentation screenshot.

Alerts in the electronic health record are important to identifying a case of AKI earlier. Dr. Kashani reviews these “sniffers” for clinicians to better understand the intent of the alerts and therefore provide the best care to patients.

Recorded November 2021

Preventing Medication-Induced AKI: the NINJA Quality Improvement Program


Learn more about NINJA (Nephrotoxic Injury Negated by Just-in time Action). This program, developed by Dr. Goldstein and colleagues, scans medication profiles in electronic health records in near-real time to identify children at risk for AKI. Pharmacists, who are coordinating with the clinical teams, receive notifications from the scan helping to reduce nephrotoxic injury. This educational video is just one example of AI machine learning to improve patient care.

Recorded November 2021

Uncovering the Ways in which AI Captures and Propagates Bias Karandeep Singh, MD, MMSc

AKI!Now_Uncovering bias

During this session, Dr. Singh explains what defines bias and how biases can be learned. He shares important work that is underway to ensure fairness in AI algorithms in order for clinicians to better manage and prevent AKI.

Recorded April 2022