Artificial intelligence (AI) in healthcare is a potentially revolutionary tool to achieve improved healthcare outcomes while reducing overall health costs. While many exploratory results hit the headlines in recent years there are only few certified and even fewer clinically validated products available in the clinical setting. This is a clear indication of failing translation due to shortcomings of the current approach to AI in healthcare. In this work, we highlight the major areas, where we observe current challenges for translation in AI in healthcare, namely precision medicine, reproducible science, data issues and algorithms, causality, and product development. For each field, we outline possible solutions for these challenges. Our work will lead to improved translation of AI in healthcare products into the clinical setting

中文翻译：

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医疗保健中的人工智能：迷失在翻译中？

医疗保健领域的人工智能 (AI) 是一种潜在的革命性工具，可在降低整体健康成本的同时实现改善的医疗保健结果。虽然近年来许多探索性结果成为头条新闻，但在临床环境中可用的认证产品甚至更少。由于当前医疗保健人工智能方法的缺陷，这清楚地表明翻译失败。在这项工作中，我们强调了我们观察到当前医疗保健 AI 翻译面临的挑战的主要领域，即精准医学、可重复科学、数据问题和算法、因果关系以及产品开发。对于每个领域，我们都概述了应对这些挑战的可能解决方案。我们的工作将改善医疗保健产品中的人工智能向临床环境的转化