摘要
一位新闻记者兼机器人与机器学习的新闻编辑每日新闻-移植药物的新研究-肾脏移植是一篇报道的主题。根据NewsRx记者来自荷兰鹿特丹的新闻，研究表明："多年来，固体器官移植的研究利用了大量的医学数据采集和人工智能(AI)和机器学习G(ML)的使用来回答诊断、预后和治疗问题。然而，尽管人工智能模型是否为传统的建模方法增加了价值的问题。如回归模型，其"黑匣子"性质是阻碍从研究转化为临床实践的因素之一。我们的新闻记者从鹿特丹大学医学中心的研究中获得了一句话：“为了提高医疗决策支持的透明度，我们开发了几种让胡理解这些模型的技术。这些技术应该有助于人工智能缩小理论和实践之间的差距，让医生和病人对模型产生信任，允许模型审计。”但这也发生在肾移植领域吗?本文报道了“黑盒”模型在诊断和预测肾移植排斥反应、移植肾功能延迟、移植肾衰竭和其他相关结果方面的应用和解释。我们强调椎间盘讨论需要（或不需要）解释ML模型在肾移植中的生物学发现和临床实施。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Transplant Medicine - Kidney Transplants is the subject of a report. According to news originating fro m Rotterdam, Netherlands, by NewsRx correspondents, research stated, “Research o n solid organ transplantation has taken advantage of the substantial acquisition of medical data and the use of artificial intelligence (AI) and machine learnin g (ML) to answer diagnostic, prognostic, and therapeutic questions for many year s. Nevertheless, despite the question of whether AI models add value to traditio nal modeling approaches, such as regression models, their ‘black box’ nature is one of the factors that have hindered the translation from research to clinical practice.” Our news journalists obtained a quote from the research from University Medical Center Rotterdam, “Several techniques that make such models understandable to hu mans were developed with the promise of increasing transparency in the support o f medical decision-making. These techniques should help AI to close the gap betw een theory and practice by yielding trust in the model by doctors and patients, allowing model auditing, and facilitating compliance with emergent AI regulation s. But is this also happening in the field of kidney transplantation? This revie w reports the use and explanation of ‘black box’ models to diagnose and predict kidney allograft rejection, delayed graft function, graft failure, and other rel ated outcomes after kidney transplantation. In particular, we emphasize the disc ussion on the need (or not) to explain ML models for biological discovery and cl inical implementation in kidney transplantation.”
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