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“The nice thing about AI is that it never gets tired. So as we think about AI replacing radiologists, let's focus on AI replacing the tedious, humdrum, boring stuff that needs to be done very well. That's where AI has the greatest opportunity."
- Dr. Brad Erickson, MD, PhD, Mayo Clinic at fireside chat at RSNA

Paige, the global leader in end-to-end digital pathology solutions and clinical AI applications, was able to improve their model's F1 score from .6 to .83 and complete annotation 10 x faster by working with Centaur Labs to annotate their pathology slide dataset.

Our new Research product enables researchers to use our platform and labeling network for free, and our new APIs allow model developers to integrate our data annotation capabilities into their ML pipelines.

At RSNA we announced our Radiology AI Safety initiative in partnership with deepc and Segmed. Together we’ll make it easier to both identify opportunities to improve models and get the data to quickly retrain them.
From new research and regulatory approvals, to new datasets, here are some of our favorite updates in AI in healthcare.
Whether you're -
...Centaur Labs can help accelerate and improve your data annotation process.
Share the resources you're using, the research you're reading and publishing, and the roles you're hiring for and we’ll share with the community next month.
Until next month,
Erik and the Centaur Labs team
Content moderation depends on more than AI automation—it requires high-quality training data. Centaur.ai delivers expert-labeled, multimodal datasets that help platforms detect hate speech, disinformation, explicit content, and compliance risks. By combining human insight with scalable infrastructure, Centaur.ai builds safer, more ethical, and more adaptable moderation systems.
Medical vibe monitoring makes AI annotation observable, measurable, and audit-ready. By tracking expert performance, consensus reliability, and pipeline health in real time, healthcare AI teams can detect labeling errors early, improve data quality, accelerate annotation throughput, and meet regulatory requirements with confidence using Centaur’s competitive expert network and observability infrastructure.
Emphasized the importance of data curation practices in reducing bias in medical AI, promoting diverse datasets, expert collaboration, and fairness metrics for more equitable outcomes.