Healthcare AI startup Agamon raises $3m to transform clinical text into data

The inability of today’s computers to understand doctors’ unique way of writing has been a major issue. Doctors can correctly describe an ‘infiltrating mass’ without writing the word ‘tumor’ or write ‘bilateral ground glass peripheral opacity’ without explicitly indicating a suspicion for COVID-19. This language is effective for fast and efficient note-taking, which is critical, but makes tracking and managing treatments impossible for a computer. This is where our Natural Language Understanding and AI come in; our software accurately and rapidly trains hospital computers to “read” doctors’ clinical reports.

Agamon has built advanced AI and NLP that assess the significance of findings extracted from unstructured medical text, starting with radiology reports. This helps us make sure no important clinical recommendation ever falls through the cracks, and will assist with automating timely review of large report volumes.

We’re delighted to back Michal and the Agamon team as we continue to invest in data driven healthcare start-ups. We’re excited by Agamon’s ability to automate the interpretation of medical text and therefore enable products such as automatic follow up and patient friendly reports. Applications at the intersection of machine learning and healthcare data are helping drive much needed change in our healthcare systems and are a core part of our investment thesis at MMC.