Article Text

Download PDFPDF
Other possible perspectives for solving the negative outcome penalty paradox in the application of artificial intelligence in clinical diagnostics
  1. Hongnan Ye
  1. Beijing Alumni Association of China Medical University, Beijing, China
  1. Correspondence to Mr Hongnan Ye, Beijing Alumni Association of China Medical University, Beijing, China; juventus_buffon{at}


Artificial intelligence (AI), represented by machine learning, artificial neural networks and deep learning, is impacting all areas of medicine, including translational research (from bench to bedside to health policy), clinical medicine (including diagnosis, treatment, prognosis and healthcare resource allocation) and public health. At a time when almost everyone is focused on how to better realise the promise of AI to transform the entire healthcare system, Dr Appel calls for public attention to the AI in medicine and the negative outcome penalty paradox. Proposing this topic has deepened our thinking about the application of AI in clinical diagnostics, and also prompted us to find more effective ways to integrate AI more effectively into future clinical practice. In addition to Dr Appel’s insightful advice, I hope to offer three other possible perspectives, including changing public perceptions, re-engineering clinical practice processes and introducing more stakeholders, to further the discussion on this topic.

  • Decision Making
  • Philosophy- Medical
  • Public Policy

Statistics from

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.


  • Contributors HY is the sole author and solely responsible for the content of this manuscript.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer-reviewed.

Linked Articles