Automated real-time assessment of intracranial hemorrhage detection AI using an ensembled monitoring model (EMM) - Takeaways - MDSpire

Automated real-time assessment of intracranial hemorrhage detection AI using an ensembled monitoring model (EMM)

  • By

  • Zhongnan Fang

  • Andrew Johnston

  • Lina Y. Cheuy

  • Hye Sun Na

  • Magdalini Paschali

  • Camila Gonzalez

  • Bonnie A. Armstrong

  • Arogya Koirala

  • Derrick Laurel

  • Andrew Walker Campion

  • Michael Iv

  • Akshay S. Chaudhari

  • David B. Larson

  • October 16, 2025

  • 0 min

Share

  • 1

    The Ensembled Monitoring Model (EMM) provides real-time confidence assessments for AI predictions in radiology without needing access to internal AI components.

  • 2

    EMM was tested on intracranial hemorrhage detection using a dataset of 2919 studies, demonstrating its ability to categorize AI prediction confidence.

  • 3

    The framework aims to reduce cognitive burden on physicians by helping them identify low-confidence AI predictions and suggesting appropriate actions.

  • 4

    EMM operates independently of the primary AI model, enhancing trust and accuracy in AI-assisted diagnoses while addressing safety concerns.

  • 5

    Key considerations for implementing EMM in clinical settings include technical aspects and best practices for effective real-time monitoring.

Original Source(s)

Automated real-time assessment of intracranial hemorrhage detection AI using an ensembled monitoring model (EMM)

  • by Zhongnan Fang, Andrew Johnston, Lina Y. Cheuy, Hye Sun Na, Magdalini Paschali, Camila Gonzalez, Bonnie A. Armstrong, Arogya Koirala, Derrick Laurel, Andrew Walker Campion, Michael Iv, Akshay S. Chaudhari, David B. Larson

  • October 16, 2025

Related Content

Interpretable deep learning for multicenter gastric cancer T staging from CT images

STD-Net: a spatio-temporal decoupling network for multiphasic liver lesion segmentation and characterization

PAM: a propagation-based model for segmenting any 3D objects across multi-modal medical images