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Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System

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BreastScreening-AI: Evaluating medical intelligent agents for human-AI interactions.

Francisco Maria Calisto¹, Carlos Santiago¹, Nuno Nunes²

¹Institute for Systems and Robotics, Avenida Rovisco Pais 1, 1049-001 Lisbon, Portugal.

Artificial Intelligence in Medicine

|April 17, 2022

Summary

BreastScreening-AI, a novel deep learning tool, significantly improved multimodal breast image classification. The Clinician-AI scenario reduced false positives by 27% and false negatives by 4%, enhancing diagnostic accuracy.

Keywords:

Artificial intelligence Breast Cancer Healthcare Human-computer interaction Medical imaging

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Area of Science:

Medical Imaging
Artificial Intelligence in Healthcare
Clinical Decision Support

Background:

Multimodal breast image classification is crucial for early cancer detection.
Integrating Artificial Intelligence (AI) into clinical workflows presents challenges and opportunities.
Evaluating clinician interaction and AI impact is vital for successful adoption.

Purpose of the Study:

To develop and evaluate BreastScreening-AI for multimodal breast image classification.
To compare diagnostic performance between a Clinician-Only and a Clinician-AI scenario.
To assess clinician acceptance, AI impact, and potential benefits in a real clinical setting.

Main Methods:

Development of BreastScreening-AI using a deep learning method.
Implementation in two scenarios: Clinician-Only and Clinician-AI.
Extensive evaluation with 45 clinicians across nine institutions, including patient selection and qualitative/quantitative analysis.

Main Results:

The Clinician-AI scenario demonstrated superior diagnostic performance.
A 27% decrease in False-Positives and a 4% decrease in False-Negatives were observed with AI assistance.
91% of clinicians reported positive impacts on expectations and satisfaction, with a 3-minute reduction in diagnosis time per patient.

Conclusions:

The integration of AI in breast cancer screening significantly enhances diagnostic accuracy and efficiency.
BreastScreening-AI positively influences clinician perception and satisfaction.
AI-assisted systems show potential to mitigate clinical errors and improve patient outcomes.