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Donor Disposition AI Model to Predict Transplant for Recovered Deceased Donor Kidneys

Organization: MST, SLU, Valiant AI
Journey Stage: (Q) Organ Offered to Center
Organization Type: Vendor / Corporate Partner
Use Case(s): Allocation

Purpose: Current practice for accelerated kidney placements rely heavily on the Kidney Donor Profile Index (KDPI) to determine if recovered deceased-donor (DD) kidneys are hard-to-place. A neural network model using DD disposition is trained to predict Not Transplanted (perfect correlation with discard) or Transplanted based on features beyond those used to calculate KDPI. These models may aid Organ Procurement Organizations (OPOs) in quickly identifying hard-to-place kidneys for early accelerated placement.

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Key Contact:

Richard
Threlkeld •
CEO

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