Artificial Intelligence in Healthcare: Lost In Translation?
  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
