technology
Not all evidence is created equal: Machine-Reading in Biomedicine
Teaching computers how to read and understand biomedical publications for cause and effect relationships is a challenging task. This is especially true for it might not be intuitive what we mean by "read" and "understand".
Point of View
Knowledge emergence - what we learn from 100K monthly publications
Every month we process more than 100,000 scientific documents. New knowledge is emerging every month across thousands of scientific disciplines
use case
How to read 35,000 articles in 1 minute
Rapid search for causes of anxiety at super human speed using the Causaly machine-reading platform
announcement
Causaly Raises $1 Million Seed Round to Deliver AI for Cause & Effect Discovery in Biomedicine
Causaly Inc., an AI for Biomedical cause & effect discovery, announces today the completion of a $1m seed round led by Marathon Venture Capital.