Case Study · Digital Pathology & AI
AI-Assisted Digital Pathology Platform Study
14 markets · Pathologists & laboratory staff
Markets
14
Quantitative
250 surveys
Qualitative
65 interviews
Focus
AI adoption
Project overview
At a glance
Separately recruited diagnostic pathologists and sample-processing laboratory staff for a digital-health company assessing adoption of AI-assisted pathology tools.
- Audience
- Pathologists, histopathologists and cytopathologists, laboratory directors and managers, histology technicians, pathology technologists, biomedical scientists and hospital IT decision-makers.
- Markets
- USA · Canada · UK · Germany · France · Switzerland · Netherlands · Sweden · Japan · South Korea · China · India · Singapore · Australia
- Methodology
- 250 online surveys plus 45 pathologist IDIs and 20 laboratory-staff interviews, with concept testing and workflow evaluation.
The brief
Understand how pathologists and laboratory professionals perceive the adoption of AI-assisted pathology tools, distinguishing those who interpret results from those who prepare and process samples.
Research focus
What the study explored
- Digital pathology adoption
- AI acceptance
- Diagnostic confidence
- Workflow integration
- Image quality
- Accuracy
- Explainability
- Validation
- IT infrastructure
- Regulatory concerns
How Yamada delivered
Delivered as one coordinated sequence
- 01Multi-market feasibility
- 02Precise interpreter-vs-processor screening
- 03Separate recruitment of both groups
- 04Professional validation
- 05Fieldwork coordination
- 06Quality control before delivery
Quality controls
Quality controls applied on this project
Only the checks this engagement required — selected by audience, methodology and risk profile.
- 01Clear distinction between pathologists and lab staff
- 02Role validation
- 03Function screening
- 04Centralised QC
Outcome
What the research delivered
The research identified different adoption barriers among clinical decision-makers and laboratory users and helped refine the product proposition, training and implementation strategy.
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Project examples are representative engagements. Client identities and commercially sensitive details are withheld where required.
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