Precision in the Face of Noise -- Lessons from Kahneman, Siboney, and Sunstein for Radiation Oncology

TL;DR

This paper explores how judgment noise affects radiation oncology, drawing on psychological insights to propose strategies like AI tools and judgment aggregation to reduce variability and improve clinical accuracy.

Contribution

It connects psychological theories of noise to radiation oncology, introducing practical methods to mitigate judgment variability in clinical practice.

Findings

Noise significantly impacts contouring accuracy in radiation therapy

AI tools and judgment aggregation can reduce variability

Practical strategies improve clinical decision consistency

Abstract

In this manuscript, we draw on the insights from Kahneman, Sibony, and Sunsteins influential nonfiction book Noise: A Flaw in Human Judgment to explore the concept of unwanted variability in judgment (i.e., noise). We introduce key terms and connect these insights to the field of radiation oncology by illustrating how noise contributes to errors in clinically relevant areas such as contouring. Additionally, we propose practical strategies to reduce noise in radiation oncology, such as through judgment aggregation and the use of artificial intelligence tools, building on the principles outlined in the book.