Artificial Intelligence in Medicine: Chances and Challenges for Wide Clinical Adoption.

ABSTRACT:

Background

Artificial intelligence (AI) applications that utilize machine learning are on the rise in clinical research and provide highly promising applications in specific use cases. However, wide clinical adoption remains far off. This review reflects on common barriers and current solution approaches.

Summary

Key challenges are abbreviated as the RISE criteria: Regulatory aspects, Interpretability, interoperability, and the need for Structured data and Evidence. As reoccurring barriers of AI adoption, these concepts are delineated and complemented by points to consider and possible solutions for effective and safe use of AI applications.

Key messages

There is a fraction of AI applications with proven clinical benefits and regulatory approval. Many new promising sy

SUBMITTER: Varghese J 

PROVIDER: S-EPMC7768160 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature