Session description:
In this session attendees will learn the current state of the art in terms of proteomic and metabolomic analysis of the kidney as it pertains to acute kidney injury and to chronic kidney disease. The role of newer machine learning and artificial intelligence tools to power discovery and interpretation of kidney biopsies will be explained. The evolving landscape of the genetic basis to kidney disease, including new genetic approaches through genomic approaches will also be featured. These new technologies provide fertile ground for new understanding of kidney diseases and kidney pathology.
Learning objectives:
Understanding the latest technology in protein and metabolic signaling that have become available for kidney disease. Appreciation of the role of automated interpretative technologies such as machine learning algorithms in metabolomic and proteomic medicine. To understand how molecular genetic techniques can be used to aid in diagnosis and management of people living with kidney disease.
| Time | Session |
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2:15 p.m.
2:33 p.m.
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Deciphering the Molecular Development of Kidney Disease: Transition From AKI to CKD
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2:33 p.m.
2:51 p.m.
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KidGen Consortium - Integrating Genomic Medicine Into Care
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2:51 p.m.
3:09 p.m.
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Metadata Ontology, Knowledge Integration, and Kidney Precision Medicine
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3:09 p.m.
3:27 p.m.
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Kidney Health Professionals and AI - Pioneers or Passive Users?
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3:27 p.m.
3:45 p.m.
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Q&A
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