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Description

Abstract: Data visualization and machine learning are increasing being adopted to analyze biomedical datasets in translational research. With the goal of guiding a researcher to relevant visualization methods and learning models, we have developed SPIRIT-SA, a comprehensive scientific analytics platform. Rule-based criteria derived from data provide visualization techniques and machine learning algorithms recommendations to a user enabling seamless biomedical data analysis.

Learning Objective 1: Gain better insight to processing raw data.

Learning Objective 2: Selecting appropriate technique to visualize a given dataset.

Learning Objective 3: Choosing machine learning models to recommend for analyzing a given dataset.

Authors:

Leslie Sim, City of Hope
Charlotte Cheng, City of Hope
Ajay Shah, City of Hope
Srisairam Achuthan (Presenter)
City of Hope

Presentation Materials:

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