A new direction to promote the implementation of artificial intelligence in natural clinical settings
By Yunyou Huang, Zhifei Zhang, Nana Wang, Nengquan Li, M. Du, Tianshu Hao, Jianfeng Zhan. 2019
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.
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- Ryuji Hamamoto
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- Ken Takasawa
- S. Jinnai
- Kazuma Kobayashi
Citations in the corpus
- Application of Artificial Intelligence Technology in Oncology: Towards the Establishment of Precision Medicine (2020, methodology): “Approved by the FDA in May 2017, AmCAD-US (AmCad BioMed Corporation) is a software device that isualizes and quantifies the statistical distribution of backscattered sig als ech ed by tissue compositions in the body from ultrasound systems [47].”