AIMC Journal:
Clinical transplantation and research

Showing 1 to 3 of 3 articles

Artificial intelligence in preclinical nonhuman primate xenotransplantation: bridging the gap from data complexity to clinical precision.

Clinical transplantation and research
Nonhuman primate (NHP) preclinical models remain an indispensable gateway for translating xenotransplantation into human clinical trials. These models generate high-dimensional immunological, physiological, behavioral, and histopathological datasets ...

A dynamic machine learning model for predicting organ transplant success to optimize donor organ utilization and reduce costs.

Clinical transplantation and research
BACKGROUND: Organ recovery for transplantation costs approximately $40,000 per donor, yet nearly 20% of recovered kidneys ultimately go unused. Static viability scores (e.g., KDPI, DRI) provide baseline risk stratification but fail to capture dynamic...

A pilot study on the impact of large language model assistance on the evaluation of complex medical living kidney donor candidates.

Clinical transplantation and research
BACKGROUND: Large language models (LLMs) are undergoing exploration as clinical decision support tools. However, their role in complex, high-stakes transplant nephrology decisions, including potential living kidney donor candidate (pLKDC) evaluation,...