Programmatic Theme: Data Science
Abstract: Clinical assessment variation (CAV) is a common phenomenon where clinicians exhibit varying judgment in assessing a patient’s overall status or specific attributes. The causes of CAV are diverse and complex, which prohibit explaining let alone resolving the issue. Using an example application in preoperative fitness assessment, we proposed a visualization framework for CAV and showed its power in presenting the information as an intuitive map. The approach can help both understand and reduce CAV.
Learning Objective: 1. Understand the significance of clinical assessment variation (CAV)
2. Appreciate the power of data visualization in helping understand and reduce CAV
3. Get a feel on how unsupervised deep learning and visualization work together on a real dataset
Andrew Wen (Presenter)
Sungrim Moon, Mayo Clinic
Jungwei Fan, Mayo Clinic