“Get me a visualization, stat!” : Data-Driven Decision Making and the Future of Healthcare

What support do we need to make decisions with data? This question is especially critical to answer in healthcare, where the pace of technological growth has added to the complexity and volume of data, with the ultimate effect of overwhelming decision makers. My research addresses this challenge by integrating techniques from machine learning, epidemiology, human computer interaction, and data visualization to contribute novel ways of managing and analyzing data, deriving actionable insights, and supporting others to make decisions with data. In this talk, I will demonstrate the impact of this interdisciplinary approach and its contributions through examples of my work in cancer clinical genomics and public health genomic epidemiology. I will also lay out my vision for how data science and data visualization should evolve in order to better support the needs of decision makers in healthcare and beyond. Specifically, I will present ideas for how statistical approaches to data visualization can help to create representative, fair, accountable, and transparent systems that facilitate human and machine collaboration in the future. As technology continues to change the kinds and amounts of data we can interrogate, it is critical to develop relevant and robust approaches for analysis and visualization that attend to the growing complexities of data-driven decision making.

About Anamaria Crisan

Anamaria Crisan is a Vanier Canada Scholar and UBC Public Scholar in her final year of study in Computer Science at the University of British Columbia. Under the joint supervision of Dr. Tamara Munzner and Dr. Jennifer Gardy, she is researching how to visualize the heterogenous collections of genomic and public health data that support investigations of disease outbreaks.  Prior to her PhD, Ana worked as a researcher with the British Columbia Centre for Disease Control and, separately, at a Vancouver-based start-up where she was responsible for the research and development of a commercially deployed prostate cancer genomic classifier. She holds a MSc in Bioinformatics from the University of British Columbia and a BSc in Computer Science from Queen's University. You can learn more about her research on her website: https://www.cs.ubc.ca/~acrisan

Website: amcrisan.github.io/