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ASN leads the fight to prevent, treat, and cure kidney diseases throughout the world by educating health professionals and scientists, advancing research and innovation, communicating new knowledge, and advocating for the highest quality care for patients.

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Kidney Week

Advances in Research Conference: Artificial Intelligence and Implementation Science

Course Description

Machine learning (ML) as an important manifestation of artificial intelligence (AI) is a collection of computationally intensive statistical learning techniques. Recent years have seen an explosion of ML and AI tools for use in health care. While numerous advances have been made with these tools, challenges in data science, validation, calibration, security, and implementation remain essential to address. Researchers and clinicians practicing in the 2020s need greater understanding of the scientific underpinnings and pragmatic issues related to AI and big data science. Improving clinical care will require the robust application of implementation science to empirically assess the effectiveness of any proposed intervention.

In this program, experts in computational biology, ML, and informatics discuss the latest advances, facilitators, and barriers to wider implementation of AI in medicine and nephrology. Provided a foundation of key principles, terms, and applications related to AI and implementation science, participants explore the opportunities these tools can bring to improving research and clinical care in kidney diseases.

Discussion includes recent advances in these fields, as well as limitations and ethical concerns with their implementation.

All on-demand presentations will be available starting Monday, October 25. Note: There is no syllabus.

ASN designates this blended learning activity for a maximum of 12.00 AMA PRA Category 1 Credits™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

(The credits total will be updated based on actual time.)

Course Objective(s)

Upon completion of the program, the participant will be able to: 1) discuss the science and potential clinical utility of AI in various disease conditions related to nephrology; 2) identify barriers and potential solutions to the implementation of AI-based solutions in health care 3) elucidate the areas in nephrology that AI has the greatest potential to affect; 4) describe the role of implementation science in closing the gap between evidence and practice; 5) explain implementation science terminology, frameworks, methods, and application; and 6) identify barriers to implementing evidence, and form strategies to overcome these barriers.

Course Chair(s)

  • Steven G. Coca, DO, MS
  • Reem Mustafa, MD, PhD, MPH, FASN


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