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Cleanlab: Making AI Work with Messy, Real-World Healthcare and NLP Data

I’ll start the talk with an overview of cleanlab 2.0, a powerful open-source package that lets you find and fix label errors and data quality issues in *any* labeled dataset… in just a few lines of code.

Next, I’ll share a (very brief) overview of confident learning, the underlying field of theory and algorithms that make Cleanlab work under the hood.

Finally, I’ll jump into four concrete examples of how cleanlab makes AI solutions work for the NLP + Healthcare communities. Namely, (1) how companies like Amazon, Google, Tesla, and Wells Fargo used Cleanlab technology, (2) automatically correcting insurance healthcare codes, (3) real-time assistance during diagnosis by flagging when a medical health report might need review by another doctor, and (4) how cleanlab open-source was used to enable a startup to understand human emotion toward supporting patient mental health AI solutions.

The Quest for Proactive and Reactive Healthcare

Let us imagine a world where the most advanced technologies in the field of artificial intelligence and sensory systems are harnessed to...