Clean Talk | Ep 41 | Improving Treatment and Patient Outcomes Using Ai w/ Julie Sufana

Clean Talk - The State of Infection Control w/ Brad Whitchurch

In this week’s episode of Clean Talk, Julie Sufana, Chief Marketing Officer at contextflow, joins us to reveal the power of AI to help radiologists improve diagnosis and patient care!
Tune in to hear about a range of topics including:
• Julie’s background and what brought her to where she is today
• About contextflow and their mission
• How contextflow utilizes Ai to improve chest CT support with the help of deep learning
• The problem with built-up data within healthcare systems
• How easily accessing past patient images helps providers diagnose & treat patients
• The amount of image patterns contextflow allows providers to access at once
• Who best benefits from contextflow’s Ai
• Removing the misconceptions around the use of Ai
• What to expect in the future for contextflow
Originally from Munster, Indiana, Julie Sufana moved to Los Angeles to study Business Administration and Spanish at the University of Southern California (USC). After earning her degree, Julie looked for ways to utilize both the creative and analytical sides of her brain by working in education, sales and marketing while pursuing her love of acting.
In 2016, Julie moved to Vienna, Austria. She subsequently earned her Masters in Marketing from WU and landed her dream job as Chief Marketing Officer at contextflow GmbH. She's particularly well-known for her writing and presentation skills, well-honed by her years in the entertainment industry. Julie is also a certified 200-hr yoga instructor and loves teaching her colleagues after hours.
A little about contextflow: the Vienna-based startup develops clinical decision support tools with the help of deep learning: SEARCH Lung CT detects 19 patterns plus nodules in lung CTs, including those related to COVID-19. It integrates directly into your PACS and preliminary test results show it reduced average reading time by 31% when available for use as well as a trend towards improved diagnostic accuracy.
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