Molecular-based precision oncology clinical decision making augmented by artificial intelligence

The rapid growth and decreasing cost of Next-generation sequencing (NGS) technologies have made it possible to conduct routine large panel genomic sequencing in many disease settings, especially in the oncology domain. Furthermore, it is now known that optimal disease management of patients depends on individualized cancer treatment guided by comprehensive molecular testing. However, translating results from molecular sequencing reports into actionable clinical insights remains a challenge to most clinicians. In this review, we discuss about some representative systems that leverage artificial intelligence (AI) to facilitate some processes of clinicians' decision making based upon molecular data, focusing on their application in precision oncology. Some limitations and pitfalls of the current application of AI in clinical decision making are also discussed.

Automated summary

The rapid growth and decreasing cost of Next-generation sequencing (NGS) technologies have enabled large panel genomic sequencing in many disease settings; personalized cancer treatment and disease management rely on molecular testing results; systems leveraging artificial intelligence (AI) to aid clinicians' decision making processes based on molecular data are now being applied in precision oncology.