The company is planning to commercialize its cancer early detection technology initially in lung cancer and is working with NYU researchers to explore future expansions.
The paper, which is not peer-reviewed, said that use of the test as a first-step screening tool would require confirmation of more than 80 percent of its results.
The team aims to fully commercialize the 28-biomarker panel for military veterans and civilians who show early symptoms of post-traumatic stress disorder.
Using deep learning, researchers attempted to classify non-small lung cancer subtypes and predict lung adenocarcinoma mutations from histopathology slides.
The researchers built a combination nucleic acid-antibody test for the disease using an approach they said could be generally useful for rapid test development.
Collaborators have created an atlas that compares available PD-L1 IHC assays and reveals areas of debate, including challenges encountered by clinicians.
