Hallucinations in medical devices

TL;DR

This paper defines hallucinations in medical devices as plausible errors that can impact clinical tasks, providing a universal framework to evaluate and mitigate such errors across various medical applications.

Contribution

It introduces a practical, universal definition of hallucinations in medical devices, linking theoretical and empirical insights to improve evaluation and reduction methods.

Findings

Proposes a universal definition of hallucinations in medical devices.

Connects hallucination definition to evaluation methodologies.

Discusses approaches to minimize hallucinations.

Abstract

Computer methods in medical devices are frequently imperfect and are known to produce errors in clinical or diagnostic tasks. However, when deep learning and data-based approaches yield output that exhibit errors, the devices are frequently said to hallucinate. Drawing from theoretical developments and empirical studies in multiple medical device areas, we introduce a practical and universal definition that denotes hallucinations as a type of error that is plausible and can be either impactful or benign to the task at hand. The definition aims at facilitating the evaluation of medical devices that suffer from hallucinations across product areas. Using examples from imaging and non-imaging applications, we explore how the proposed definition relates to evaluation methodologies and discuss existing approaches for minimizing the prevalence of hallucinations.