Artificial intelligence and transplanting the elderly.

Area of Science:

• Medicine
• Computer Science
• Biotechnology

Background:

• The increasing number of older organ donors and recipients presents unique challenges in transplantation.
• Artificial intelligence (AI) offers potential solutions to enhance organ allocation, retrieval, and transplantation processes.

Purpose of the Study:

• To explore the application of AI in organ transplantation, particularly for elderly donors and recipients.
• To identify current gaps and future directions for AI in geriatric organ transplantation.

Main Methods:

• Review of existing AI applications in organ transplantation.
• Analysis of how age is currently considered in machine learning models for transplantation.
• Identification of data requirements for developing specialized AI models.

Main Results:

• AI has not been specifically focused on older donors or recipients in transplantation research.
• Age is typically treated as a continuous variable in current machine learning prediction models.

Conclusions:

• Dedicated datasets and standardized data exchange protocols are needed for elderly donors.
• Ex vivo machine perfusion data is crucial for assessing organ suitability in elderly donors.
• AI models for elderly recipients should incorporate post-transplant complications, especially cardiovascular ones, to predict patient outcomes.