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[ China Pharmaceutical Network Technology News ] It is reported that Jones, director of the Austin Liver Transplant Health Center in Melbourne, Australia, and his colleague Lawrence Lau have developed an algorithm that can help medical institutions better match organ donors and organ recipients. They plan to use specially designed artificial intelligence programs to improve the accuracy of liver transplant matching, thereby minimizing graft failure and patient death.
(Artificial Intelligence Medicine Breaks Through AI Can Help Organ Transplant Matching Prediction Image Source: Baidu Pictures)
Looking back on 1988, when Bob Jones was doing a liver transplant, he must have thought that he would be interested in artificial intelligence after 29 years.
Jones is the director of the Austin Liver Transplant Health Center in Melbourne, Australia, and he and his colleague Lawrence Lau have developed an algorithm that can help medical institutions better match organ donors and organ recipients. Jone said they plan to use specially designed artificial intelligence programs to improve the accuracy of liver transplant matching, thereby minimizing graft failure and patient death.
His team imported about 25 donor and receptor features into artificial intelligence programs, using data points to predict recovery after organ transplantation.
“This machine learning algorithm can predict matching results by learning the characteristics of multiple donors and receptors,†he explains. “We use basic information such as gender, age, underlying disease, blood type, plus certain characteristics about donors. Important information such as liver rejection parameters."
Using artificial intelligence to assess the postoperative status of 75 adult liver transplant patients, they found that AI predicted a graft failure accuracy of 84% after 30 days of transplantation, compared with 68% by conventional methods.
“This is the first time that really means that we can use a quantitative approach to assess the applicability of organs.†He added, “Contrary to current methods, this can be attributed to examining all data based on doctor experience and then making a diagnosis. â€
Jones said that they have already submitted the results of this research to many academic journals, and the next step will be a prospective randomized trial.
Jeremy Chapman, director of kidney transplantation at Westmead Hospital in Australia and board member of the Australian Organ Transplant Association, said that the preliminary results of the experiment seem to be very positive. But he stressed that this research can only be applied to the earliest stages, that is, to help decision-making rather than determine the final surgery or not.
He also suggested that the algorithm may not be immediately applicable to other regions, because in Melbourne, the team led by Jones led the algorithm in a way that might have specific features not available in other regions.
As a kidney transplant expert, he added that the organ transplant system should not only consider the results of surgical predictions, but also consider factors such as fairness, optimal organ use, and so on.
“You can easily improve the results of organ transplants by removing the organ from the most appropriate donor and putting it in the most appropriate recipient,†Chapman said. “Use our past transplant results data and pass Optimizing the fair distribution system, we can improve the status of organ transplantation step by step."
In response to Chapman's assessment, Jones emphasized that their projects are in a "very early stage," but they are interested in the in-depth forecasting process, including those that are not easily quantified. However, Jones also admits that they have some commonalities in setting parameters, but sometimes a number does not fully express the patient's condition.
But in any case, for Jones, the application of new technology undoubtedly shows that the future of organ transplantation will be exciting.