Presented by:

I'm a co-founder and CTO of Segmed.ai. Previously I held senior engineering roles at Salesforce, Twin Prime (that Salesforce acquired), and Xilinx. I have been a PostgreSQL user for nearly a decade now. I live in Bay Area, California.

No video of the event yet, sorry!

Receiving, de-identifying and processing medical data pose many challenges in the real-world. Non-uniformity, multitude of formats, lack of structure and a volume of data create unique problems in data storying, querying and management. Careful separation of sensitive data is required at all times, and retaining this separation ends with some interesting design problems. In this talk we present a path we took at Segmed to build a highly scalable, ML-enabled de-identified data warehouse, where we use PostgreSQL and Go to build an engine for processing and de-identifying medical text and image data.

Date:
2022 April 7 16:40 PDT
Duration:
20 min
Room:
Santa Clara
Conference:
Silicon Valley 2022
Language:
Track:
Data
Difficulty:
Medium