Research output per year
Research output per year
Project Details
Description
To develop evidence-based methods to guide the implementation of AI systems into clinical services, we will undertake foundational research to characterise the most significant health service features impacting AI performance and develop new methods and tools to proactively monitor clinical AI to minimise patient harm and maximise outcomes.
| Status | Active |
|---|---|
| Effective start/end date | 1/01/22 → 31/12/26 |
Research output
- 1 Abstract
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DeepMIIC: a deep-learning-based framework for whole-slide multiplex immunofluorescence image classification
Rana, P., Gide, T. N., Adegoke, N. A., Mao, Y., Long, G., Scolyer, R. A., Wilmott, J. S., Berkovsky, S., Coiera, E. & Liu, S., 30 May 2024. 1 p.Research output: Contribution to conference › Abstract › peer-review