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EVENT DETAILS |
Tonights Meetup features a triple-hitter of talks on R in medicine, biostats & health tech. Each speaker will talk for roughly 20 minutes about the topics below, before & after a half hour of socializing & snacks at Flatiron Health. Please RSVP before Wednesday, Nov 13.
Speakers:
Jacqueline Gutman, Data Scientist, Flatiron Health
Jessica Streeter, Data Scientist, Spring Health
Sam Adhikari, Assistant Professor, Biostatistics, NYU School of Medicine
Agenda:
6:00-6:25 pm Introductions & Social Time
6:30-6:35 pm R-Ladies New York Announcements
6:40-7:00 pm Survival analysis for everyone!
7:05-7:25 pm Hierarchical Models for Survival Analysis with Spatial Risk Factors in R
7:30-7:50 pm Simplified Data Quality Monitoring of Dynamic Longitudinal Data
7:55-8:00 pm Community Announcements
8:00-8:30 pm Networking
Talk 1: Simplified Data Quality Monitoring of Dynamic Longitudinal Data
Ensuring the quality of data we deliver to customers or provide as inputs to models is often one of the most under-appreciated & yet time-consuming responsibilities of a modern data scientist. When we have access to dynamic, longitudinal, continuously updating data, that complexity can become an asset. We will demonstrate how to to simplify data quality monitoring of dynamic data with a functional programming approach that enables early & actionable detection of data quality concerns. Using purrr as well as tidyr & nested tibbles, we will illustrate the five key pillars of enjoyable, user-friendly data quality monitoring with relevant R code: Readability, Reproducibility, Efficiency, Robustness, & Compositionality.
Speaker 1: Jacqueline Gutman is a data scientist on the Quantitative Sciences team at Flatiron Health, supporting cancer research & improving patient care by working with electronic health record data & building accessible data science tools for reproducible research. Prior to joining Flatiron, she worked as a data scientist at Plated & at NYU School of Medicine, & holds a Master's in Data Science from New York University.
Talk 2: Survival analysis for everyone!
When people initially think of survival analysis, they usually think of terminal diseases & mortality. But it had much broader applications in the medical field. I'll be giving a brief overview of survival analysis, it's applications in a behavioral health managed care setting, & some tips on communicating these results to clinical teams.
Speaker 2: Jessica Streeter is a Data Scientist at Spring Health, & a medical sociologist turned data scientist. She has spent her career working in the behavioral health space, including in direct care at an inpatient psychiatrist hospital. She lives in Philly with her wife, their son, & their 3 dogs, & she loves jiu jitsu, craft beer, & horror movies.
Talk 3: Hierarchical Models for Survival Analysis with Spatial Risk Factors in R
Observations within a community are more likely to be correlated than those from different communities. Hierarchical models with random effects are often built to account for such correlation. In this talk, I will focus on spatial hierarchical models in the context of survival data. I will review survival model with random frailties, to account for clustering within a community, & its extension to account for autocorrelation between frailties of neighboring communities.
Speaker 3: Sam Adhikari an assistant professor of Biostatistics in the Department of Population Health, NYU School of Medicine. Her research interest lies in developing & implementing statistical & machine learning tools to solve problems motivated by real world applications in medicine, global health & education. Her methodological work has focused on statistical social network analysis, penalized regression for longitudinal data & Bayesian causal inference methods. In her leisure time, Sam likes to run, do yoga & go to comedy shows.
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