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Likelihood Systems Can Improve Hit Rates in Low-Prevalence Visual Search Over Binary Systems.

Tobias Rieger1, Benita Marx1, Dietrich Manzey1

  • 1Technische Universität Berlin, Germany.

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Likelihood decision support systems improve visual search accuracy in low-prevalence scenarios. These systems enhance hit rates without increasing false alarms, offering a promising solution for tasks like medical imaging.

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human–automation interaction, visual search, decision making, trust in automation, compliance and reliance, radiology and medical imaging

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Area of Science:

  • Human-Computer Interaction
  • Cognitive Psychology
  • Information Science

Background:

  • Low target prevalence in visual search tasks, such as medical imaging and security screening, often results in low hit rates.
  • Traditional binary decision support systems generate numerous false alarms in low-prevalence settings, limiting their effectiveness.
  • Likelihood-based systems offer enhanced certainty information, potentially improving performance without exacerbating false alarms.

Purpose of the Study:

  • To compare the performance of binary versus likelihood decision support systems in low-prevalence visual search tasks.
  • To determine if likelihood systems can increase hit rates without a corresponding rise in false alarms.

Main Methods:

  • A simulated medical search task was employed with a low target prevalence.
  • Participants completed the task across two sessions, each supported by either a binary or a likelihood decision support system.
  • Interaction involved sequentially uncovering stimulus parts using a mouse interface.

Main Results:

  • Participants achieved higher hit rates when using likelihood decision support systems compared to binary systems.
  • The observed increase in hit rates with likelihood systems occurred without a significant increase in false alarm rates.
  • This suggests likelihood systems are effective in improving detection accuracy.

Conclusions:

  • Likelihood decision support systems present a viable solution for addressing the challenges of low-prevalence visual search.
  • These systems can enhance transparency by providing clear indications of system certainty.
  • The findings suggest that providing simple, interpretable certainty information is key to improving performance in domains like radiology.