  Artificial intelligence (AI) researchers claim that they have made great
`achievements' in clinical realms. However, clinicians point out the so-called
`achievements' have no ability to implement into natural clinical settings. The
root cause for this huge gap is that many essential features of natural
clinical tasks are overlooked by AI system developers without medical
background. In this paper, we propose that the clinical benchmark suite is a
novel and promising direction to capture the essential features of the
real-world clinical tasks, hence qualifies itself for guiding the development
of AI systems, promoting the implementation of AI in real-world clinical
practice.
