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AIM-HER2 Breast Cancer

AI-based Measurement of HER2 Scoring


AIM-HER2 delivers automated and reproducible digital HER2 scoring with explainable AI heatmap visualizations. Now available on the AISight Image Management System.1


AIM-HER2 cells slide scan

Confidently score HER2

Accurate and reproducible HER2 scoring to assist pathologists, especially in reviewing borderline cases and HER2 low expression.

Streamline your workflow

Multi-scanner compatibility plus automated whole slide image analysis and control tissue identification — no manual ROI selection.

Interpret and Explain

Additive MIL based heatmaps2 highlight features that drive HER2 score prediction, enabling human pathologist explainability.

Specifications

  • Intended Use: Research Use Only
  • Indications: Breast Cancer
  • Clones: Ventana 4B5 and Dako HercepTest
  • Scanners: Leica Aperio® AT2 and GT450; Hamamatsu NanoZoomer® s360
  • Inputs: Breast cancer biopsy, resection, and/or excision sample from primary, recurrent, or metastatic tumor (excluding in situ tumor)
  • Outputs: HER2 score (0, 1+, 2+, 3+); Area of invasive carcinoma; Additive multiple instance learning (aMIL) density heatmap

AIM-HER2 Breast Cancer may be compatible with additional scanner types. Please contact us for more information.

HER2 IHC slide platform view

AIM-HER2 Scoring Heatmaps


Additive MIL based heatmaps2 highlight tissue patterns features that most contribute to AIM-HER2's score prediction. Pathologists are able to more confidently assess HER2 expression, especially in borderline cases with more slide-level heterogeneity as they can quickly and more easily focus on the most critical features and slide areas.




“I like that these heatmaps correlate to the likelihood that the region is a particular score. It gives me the immediate intuition as to the parts of the slide I should focus on.”

— Health System Pathologist, UK Cancer Center




Rigorously trained and tested

>157K

Annotations

12K

Slide-level HER2 scores

4K

Slides

65+

Board-certified breast pathologists

Resources

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1AIM-HER2 is for Research Use Only. Not for use in diagnostic procedures.
2 Javed, et al. Additive MIL: Intrinsically Interpretable Multiple Instance Learning from Pathology. Computer Vision and Pattern Recognition, June 2022. arXiv:2206.01794