Data Science in 30 Minutes: Medical Metrics that Matter – The Partnership Between Data Science and the Medical Field


The medical field has been one of the fastest adopters of new data science technology. Finding new ways to treat and manage patient health has become a growing industry for data science.

On Wednesday, February 19th, at 5PM ET, we chatted with Bill Lynch, lead data scientist at NeuroFlow, as he discussed the way his team and company are revolutionizing the medical field with their tools. NeuroFlow has built natural language processing tools and other predictive analytics initiatives to enable their clinical customers to proactively identify and treat their highest-risk patients. This enables their users to be more efficient and deliver more personalized, measurement-based care, critical in the mental health field given the associated stigma and lack of clinical experts. Register now and learn how Bill and his team work on transforming data into insights through predictive modeling and visualization, as well as leading the data centralization, automation and system design efforts that power their data products both for their customers and their internal teams.

Download Slides

Related Blog Posts

Data-Science-Man-with-Code-scaled

The Shape of Code

The shape of code, or what we can learn from indentation. As a TDI data scientist in residence, I have learned to judge code quality at a quick glance by looking at indentation. The rule of thumb is: good code has frequent changes in indentation, but should not be deeply indented.

Read More »