Artificial intelligence can be a revolution in the kidney transplant ... "more accurate tool"

An ‘American-British’ research team has developed an advanced tool for artificial intelligence with the aim of improving forecasts associated with the results of kidney transplantation of the deceased donors. According to what is published in the kidney failure patrol, the instrument known as UK-DTOP is an important step towards improving the results of kidney transplantation using artificial intelligence. This tool is expected to contribute to the update of kidney distribution policies in the United Kingdom and the United States, which can improve patient care and use important health resources more efficiently. And if this instrument is adopted worldwide, a revolution can occur in the operation of organ transplants, which can save more lives and improve the quality of life of kidney transplant patients. For patients with renal failure in the late stage, kidney transplantation may be the process of changing life completely as it provides a new opportunity to survive and improve their quality of life compared to other treatment options. But in the UK alone, about 5,000 people await kidney transplant, and the average waiting period for a college of a dead donor is between two to three years. The power of artificial intelligence and machine learning by taking advantage of the strength of artificial intelligence and machine learning, this new system is a tool to support decision -which is more accurate and reliable than the traditional instruments used; It can improve the choice of donors, and to develop better implant strategies, leading to better results for patients. By improving how to award organs, better results for recipients can be guaranteed, and the acceptance of this tool can lead to great progress in patient care and the use of health resources. Kidney transplant is a process of underlying risk, and with the increasing demand for organs exceeding the available organs, it is necessary to ensure that every college donated is effective. However, current predictive models, such as the risk of kidney donors, show a limited accuracy in their accurate prediction of patients’ health results; This highlights the urgent need for more sophisticated instruments that make better clinical decisions. A group of experts from hospitals in the United States and the UK have developed a new program based on artificial intelligence; To predict the results of kidney transplantation of the deceased donors in the UK, this instrument was developed over 15 years using approximately 30,000 kidney transplants. According to the lead author of the study, “Hatem Ali”, a specialist in kidney disease in Kovantry and Warwikchire hospitals, the UK, his team believes that this model will “be a wonderful turning point in the field of kidney transplantation,” saying that “the instrument hopes to bring about a more efficient distribution of organs. The team used data from 2008 and 2022 from more than 29 thousand cases of cultivation registered in the kidney transplant record in the UK, and the performance of three advanced automatic learning models was evaluated, taking into account several factors related to donors, recipients and cultivation itself, and it was found that the new tool was the most better power of other indicators. Evaluating the results of kidney transplant and this tool can improve the choice of donors and agricultural strategies; It also works to improve the spread of organs in accordance with the needs of patients, which increases the chances of success of surgeries and reduces the failure rate, thereby improving the quality of life for patients. The instrument also helps to improve kidney allocation policies, which contribute to the optimal use of donated organs and increases the general efficiency in the health system. The co -author of the study, “Michelus Molnar”, a researcher at the University of “Utah”, says that the instrument is flexible in the field of evaluating the results of kidney transplantation of the deceased donors, and it helps to improve the decisions associated with the leading agriculture, while acknowledging that the final decision of the member’s acceptance depends. Although this tool is a great progress in predicting renal transplant results, the research team acknowledges that this tool has some restrictions, such as contrast in the reported data, the lack of information about some of the characteristics of donors, and the absence of some factors that may affect the long -term results, such as specific antibodies and some biological indicators.