Hallucinations in medical devices

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.

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Publication Details

Journal
Artificial Intelligence in the Life Sciences
Published
2025-10-25
DOI
https://doi.org/10.1016/j.ailsci.2025.100145
Citations
3
Primary Topic
Psychosomatic Disorders and Their Treatments
Type
article
Field-Weighted Citation Impact
4.41
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article

Hallucinations in medical devices

Aldo Badano, Víctor García, Jason Granstedt, Prabhat KC et al.
3 citations
Artificial Intelligence in the Life Sciences
Psychosomatic Disorders and Their Treatments
4.41
article

Hallucinations in medical devices

Aldo Badano, Víctor García, Jason Granstedt, Prabhat KC, Rucha Deshpande
article en
3 citations

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.

Artificial Intelligence in the Life SciencesVol. 8
Center for Devices and Radiological Health (US)
Openalex Percentile: Top 5%
Psychosomatic Disorders and Their Treatments
4.41
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