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With the rapid developments of digital picture processing, pattern recognition, and intelligent algorithms, artificial intelligence (AI) has been widely applied in the medical field. The applications of artificial intelligence in medicine (AIM) include diagnosis generation, therapy selection, healthcare management, disease stratification, etc. Among the applications, the focuses of AIM are assisting clinicians in implementing disease detection, quantitative measurement, and differential diagnosis to improve diagnostic accuracy and optimize treatment selection. Thus, researchers focus on creating and refining modeling processes, including the processes of data collection, data preprocessing, and data partitioning as well as how models are configured, evaluated, optimized, clinically applied, and used for training. However, there is little research on the consideration of clinicians in the age of AI. Meanwhile, AI is more accurate and spends less time in diagnosis between the competitions of AI and clinicians in some cases. Thus, AIM is gradually becoming a hot topic. Barely a day goes by without a claim that AI techniques are poised to replace most of today’s professionals. Despite huge promise surrounding this technology, AI alone cannot support all the requirements for precision medicine, rather AI should be used in cohesive collaboration with clinicians. However, the integration of AIM has created confusion among clinicians on their role in this era. Therefore, it is necessary to explore new roles for clinicians in the age of AI. |
