# Augmenting Pathologists with NaviPath: Design and Evaluation of a Human-AI Collaborative Navigation System

arXiv: https://arxiv.org/abs/2302.07309 · HTML: https://mlsanity.com/paper/2302.07309/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Feb 2023.

## Built on by (most cited first, 10 of 10)

- [PathFinder: A Multi-Modal Multi-Agent System for Medical Diagnostic Decision-Making Applied to Histopathology](https://mlsanity.com/paper/2502.08916/) (2025)
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- [Surgment: Segmentation-enabled Semantic Search and Creation of Visual Question and Feedback to Support Video-Based Surgery Learning](https://mlsanity.com/paper/2402.17903/) (2024)
- [Z-Stack Scanning can Improve AI Detection of Mitosis: A Case Study of Meningiomas](https://mlsanity.com/paper/2501.15743/) (2025)
- [Adaptive Human-Agent Teaming: A Review of Empirical Studies from the Process Dynamics Perspective](https://mlsanity.com/paper/2504.10918/) (2025)
- [Beyond the Monitor: Mixed Reality Visualization and Multimodal AI for Enhanced Digital Pathology Workflow](https://mlsanity.com/paper/2505.02780/) (2025)
- [Team Westwood Solution for MIDOG 2025 Challenge: An Ensemble-CNN-Based Approach For Mitosis Detection And Classification](https://mlsanity.com/paper/2509.02600/) (2025)
- [Within the MDT Room: Situated in Multidisciplinary Team-Grounded Agent Debate for Clinical Diagnosis](https://mlsanity.com/paper/2603.28393/) (2026)

## Abstract (arXiv)

Artificial Intelligence (AI) brings advancements to support pathologists in navigating high-resolution tumor images to search for pathology patterns of interest. However, existing AI-assisted tools have not realized this promised potential due to a lack of insight into pathology and HCI considerations for pathologists' navigation workflows in practice. We first conducted a formative study with six medical professionals in pathology to capture their navigation strategies. By incorporating our observations along with the pathologists' domain knowledge, we designed NaviPath -- a human-AI collaborative navigation system. An evaluation study with 15 medical professionals in pathology indicated that: (i) compared to the manual navigation, participants saw more than twice the number of pathological patterns in unit time with NaviPath, and (ii) participants achieved higher precision and recall against the AI and the manual navigation on average. Further qualitative analysis revealed that navigation was more consistent with NaviPath, which can improve the overall examination quality.
