---
title: Examination of Pathologist–AI Interactions and Their Impact on Pathologist Accuracy Using AI–Assisted Scoring of IHC for HER2
description: Examination of Pathologist–AI Interactions and Their Impact on Pathologist Accuracy Using AI–Assisted Scoring of IHC for HER2
---

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# [Examination of Pathologist–AI Interactions and Their Impact on Pathologist Accuracy Using AI–Assisted Scoring of IHC for HER2](https://www.pathai.com/publications/examination-of-pathologist-ai-interactions-and-their-impact-on-pathologist-accuracy-using-ai-assisted-scoring-of-ihc-for-her2)

 Written by [Admin](https://www.pathai.com/publications/author/admin) | May 6, 2026 4:00:00 AM

## Abstract

 

## Context.—

Advances in computer vision have fueled the development of artificial intelligence (AI)–based algorithms for pathology. AI-assisted approaches may streamline the diagnostic workflow and reduce variability.

## Objective.—

To assess the impact of an AI-assist model for human epidermal growth factor receptor 2 (HER2) scoring on pathologist reproducibility and accuracy and to understand pathologist-model interactions.

## Design.—

An AI-Assist algorithm for HER2 scoring, AI-Measurement of HER2 (AIM-HER2), was developed to generate slide-level scores of HER2 immunohistochemistry (IHC) aligned with guidelines from the American Society of Clinical Oncology/College of American Pathologists. AIM-HER2 was assessed in a retrospective reader study wherein HER2-trained pathologists (n = 20) scored breast cancer cases (n = 200) with and without model assistance using a 2-cohort crossover design with a 3-week washout. A separate panel of expert pathologists (n = 5) provided manual reference scores.

## Results.—

As an AI-assist tool, AIM-HER2 improved interrater agreement both overall and at the 0/1+ and 1+/2+ cutoffs and significantly increased positive percentage agreement at the 0/1+ and 1+/2+ cutoffs. Pathologists displayed a wide range of model override rates, and the quality of these overrides was correlated with each pathologist’s manual accuracy. Measurements of AIM-HER2 accuracy were highly dependent on reference panel composition.

## Conclusions.—

The use of AI-assist tools, such as AIM-HER2, for scoring HER2 IHC in breast cancer may improve pathologist reproducibility and accuracy, particularly at the 0/1+ and 1+/2+ cutoffs. However, improved consistency of pathologist interpretation of AI-assisted IHC scoring guidance may be necessary for AI-assist tools to reach their full potential.

[View Publication](https://aplm.kglmeridian.com/view/journals/arpa/aop/article-10.5858-arpa.2025-0262-OA/article-10.5858-arpa.2025-0262-OA.xml)

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