Presented By O’Reilly and Cloudera
Make Data Work
September 11, 2018: Training & Tutorials
September 12–13, 2018: Keynotes & Sessions
New York, NY
Olga Cuznetova

Olga Cuznetova
Data Scientist, Optum

Website

Olga Cuznetova is a data science team lead at Optum Enterprise Analytics, where she guides junior team members on their projects and helps implement data science solutions that address healthcare business needs. Currently, her projects focus mostly on building disease progression and clinical operations models. A few examples include predicting high-cost diabetic patients, predicting the progression tofo end-stage renal disease, implementing a substance abuse disorder model using external client data, and predicting medical prior authorization outcomes. Previously, Olga completed a one-year technology development program with a focus on the development of essential technical skills, healthcare business acumen, and an analytical skill set, which led her to choose a data science career path. Olga holds a BS in finance from Central Connecticut State University. When she has a spare moment, you can find her traveling both in the United States and abroad.

Sessions

11:20am–12:00pm Wednesday, 09/12/2018
Breaking the rules: End-stage renal disease prediction
Location: 1A 12/14 Level: Beginner
Secondary topics:  Health and Medicine
Olga Cuznetova (Optum), Manna Chang (Optum)
Average rating: ***..
(3.33, 3 ratings)
Olga Cuznetova and Manna Chang demonstrate supervised and unsupervised learning methods to work with claims data and explain how the methods complement each other. The supervised method looks at CKD patients at risk of developing end-stage renal disease (ESRD), while the unsupervised approach looks at the classification of patients that tend to develop this disease faster than others. Read more.