Deep learning is transforming the analysis of biological images, but applying these models
to large datasets remains challenging. Here we describe the DeepCell Kiosk, cloud-native …

There has been increased interest in utilizing non-invasive “liquid biopsies” to identify
biomarkers for cancer prognosis and monitoring, and to isolate genetic material that can predict …

Live-cell imaging experiments have opened an exciting window into the behavior of living
systems. While these experiments can produce rich data, the computational analysis of these …

Circulating tumor cells (CTCs) have a great potential as indicators of metastatic disease that
may help physicians improve cancer prognostication, treatment and patient outcomes. …

Concurrent advances in imaging technologies and deep learning have transformed the nature
and scale of data that can now be collected with imaging. Here we discuss the progress …

Extraction of rare target cells from biosamples is enabling for life science research. Traditional
rare cell separation techniques, such as magnetic activated cell sorting, are robust but …

Immunotherapies (IT) require induction, expansion, and maintenance of specific changes to
a patient's immune cell repertoire which yield a therapeutic benefit. Recently, mechanistic …

… Edward Pao, and Dino Di Carlo hold equity in Ferrologix, Inc., which has licensed technology
described in this article. … Coleman Murray and Edward Pao contributed equally to this work. …

Deep learning is transforming the ability of life scientists to extract information from images.
These techniques have better accuracy than conventional approaches and enable …

Cells are the fundamental unit of biological organization, and identifying them in imaging
data-cell segmentation-is a critical task for various cellular imaging experiments. While deep …