Artificial Intelligence for Quality Control in In Vitro Cell-Based Assays

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Robust, High-Throughput QC for In Vitro Assays

Auto-QC works with nearly all types of signals (csv files) and images


Flag unwanted cell types

Plate Scanning

Remove out-focus images

Patch Clamp

Detect bad signal recordings


Filter low activity


Identify noisy

How it Works

Step 1

Create a training dataset. Gather examples for valid and invalid signals or images

Step 2

Upload your training data to Auto-QC to create a model for classifying valid versus invalid.

Step 3

Download your model and use it to sort your data for new experiments.

Auto-QC is for Research Use Only

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