Receive a weekly summary and discussion of the top papers of the week by leading researchers in the field.

Avoiding bias in artificial intelligence.

In International forum of allergy & rhinology ; h5-index 34.0

Artificial intelligence (AI) is ubiquitous and expanding, and the healthcare industry has rapidly adopted AI and machine learning for numerous applications. It is essential to understand that AI is not immune to the biases that impact our clinical and academic work, and in fact may inadvertently amplify rather than reduce them. As we harness the power of AI, it is our obligation to our patients to ensure that we address these concerns. We must take responsibility for proactive stewardship to protect against bias, not only for new AI algorithms, but also for our research studies that may one day provide data for those algorithms. This article is protected by copyright. All rights reserved.

Gudis David A, McCoul Edward D, Marino Michael J, Patel Zara M

2022-Dec-27

evidence-based medicine, imaging, medical therapy of chronic rhinosinusitis, patient reported outcome measure, quality of life, simulation training, statistics