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Abstract: In this talk we will explore the world of imaging in digital pathology and discover gigapixel images and how to look at them. We will learn how deep learning can help predict cancer recurrence in the case of prostate cancer and how models can help pathologists discover new biomarkers.

Python deep learning digital pathology

Building production-ready ML systems is rarely straightforward—especially when predictions must be triggered by real-world events in near real time. In this talk, I’ll walk through how FastAPI and Pydantic can be used to architect an event-driven ML system, where model workflows are orchestrated using message queues and jobs vary in latency and compute requirements. The goal is to show how Python developers can move fast while maintaining control over validation, orchestration, and deployment in complex ML architectures.

fastapi Pydantic Python event-driven ml message queues
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