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Overcome the challenges of high-content cell analysis

Artificial intelligence (AI) can help users overcome the challenges of high-content cell analysis, improve data quality, & optimize workflow efficiency.

By using machine learning/artificial intelligence (AI) during the image analysis process, users can overcome many of the challenges that can come with high-content 3D cell analysis and better leverage  the information-rich content within an image. In addition to removing person-to-person variation, bias, and error, machine learning can substantially increase productivity, by undertaking repetitive, lengthy, and laborious tasks previously performed by staff whose time could be better used interpreting the data. Ultimately, this enables screening assays that can analyse thousands of features per cell – allowing your assays to become much more informative. 

 

IN Carta® Image Analysis Software from Molecular Devices allows you to go from assay to insights quickly and reliably, solving complex image analysis problems and turning images into robust quantitative data. Combining machine learning capabilities with a modern user experience, cutting edge technology, guided workflows, and scalable batch processing, IN Carta software minimises the learning curve and removes barriers to productivity—even when tackling complex, high-content 3D cell models, including organoids, spheroids, and more. 

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