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Detailed Course Information


Fall 2019 Semester
Aug 02, 2021
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HINF 6500 - Predictive Analytics and Modeling
Seeks to train students to transform data to useful, actionable knowledge through the use of mathematical and computational models. Reviews popular techniques for data mining and health analytics based on regression and machine-learning methodologies. Introduces students to a spectrum of models—ranging from data-driven to principle-based, mechanistic approaches—and examines how to compare models and use them to improve understanding of data. Introduces model-based methods of artificial intelligence as applied to healthcare problems, covering fundamental principles of AI and a variety of applications in healthcare.
3.000 Credit hours
3.000 Lecture hours

Levels: Graduate
Schedule Types: Lecture

Health Informatics Department

Course Attributes:
GSBV Bouve

Must be enrolled in one of the following Levels:     

Graduate level HINF 6400 Minimum Grade of C- and Graduate level DA 5030 Minimum Grade of C- and (Graduate level INSH 5301 Minimum Grade of C- or Graduate level PPUA 5301 Minimum Grade of C-)

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