Auto-QC

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





Microscopy

Flag unwanted cell types



Plate Scanning

Remove out-focus images



Patch Clamp

Detect bad signal recordings



MEA

Filter low activity
signals



Impedance

Identify noisy
signals





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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