Across the world, thousands of patients are waiting for life-saving organ transplants, but the number of donor organs is far from meeting the demand. Recently, doctors and scientists at Stanford University have developed a new artificial intelligence (AI) tool designed to reduce unnecessary waste in the organ transplant process, especially in liver transplants. According to statistics, nearly half of the donation cases are ultimately canceled before actual transplantation, due to improper timing of the donor's death after cardiac arrest.
Image source note: The image was generated by AI, and the image licensing service is Midjourney.
This AI tool uses a machine learning model to predict whether a donor is likely to die within the time frame when the organ is still suitable for transplantation. Compared to the judgment of top surgeons, this tool performs better, reducing the rate of ineffective organ retrieval by 60%, meaning that the organ was no longer usable even though the transplant surgery had already been prepared, because the donor did not die within the time limit.
Professor Kazuhide Sasaki, clinical professor of abdominal transplantation at Stanford University, said: "By identifying the potential viability of an organ before any surgical preparation begins, this model can improve the efficiency of the transplant process and has the potential to help more patients in need of organ transplants." The relevant findings of this research have been published in the journal The Lancet Digital Health.
This advancement is expected to not only reduce unnecessary work and resource waste in hospitals during the organ recovery process, but also lower medical costs. Hospitals currently mainly rely on surgeons' judgment to assess the critical timing of donors. However, due to differences in judgment criteria, it leads to significant costs and resource waste. This new AI tool is based on data from over 2,000 donors, and by analyzing neural, respiratory, and circulatory data, it can more accurately predict the donor's dying process.
Researchers said that in the future, they will promote the application of this AI tool in heart and lung transplant trials, aiming to further optimize organ utilization efficiency.
Key Points:
1. 🧠 Stanford University's AI tool can predict whether a donor will die within the time frame when the organ is still suitable for transplantation, reducing waste in the transplant process.
2. 💡 The tool performs better than surgeons in reducing the rate of ineffective organ retrieval, decreasing 60% of ineffective cases.
3. ⏳ Future plans include applying this AI tool to heart and lung transplants to further improve organ utilization efficiency.
