Assessment of Outcomes by Using Machine Learning

Shankar Rengasamy Venugopalan; Mohammed H. Elnagar; Deepti S. Karhade; Veerasathpurush Allareddy

doi:10.1007/978-3-030-71881-7_11

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Book chapter

Assessment of Outcomes by Using Machine Learning

Shankar Rengasamy Venugopalan, Mohammed H. Elnagar, Deepti S. Karhade and Veerasathpurush Allareddy

Machine Learning in Dentistry, pp.131-143

Springer International Publishing

07/25/2021

DOI: 10.1007/978-3-030-71881-7_11

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Abstract

There has been a tremendous amount of data available from multiple sources. These data can be leveraged to realize excellent clinical outcomes. In this chapter, we provide an overview of different machine learning approaches used to analyze large datasets and the different applications of machine learning tools in craniofacial genomics, imaging, and remoted dental monitoring. Machine learning has shown much promise as we move forward in the era of personalized medicine/dentistry.

CBCT

Clinical outcomes

Genomics

Machine learning

Remoted dental monitoring

Details

Title: Subtitle: Assessment of Outcomes by Using Machine Learning
Creators: Shankar Rengasamy Venugopalan - University of Iowa
Mohammed H. Elnagar - University of Illinois at Chicago
Deepti S. Karhade - University of North Carolina at Chapel Hill
Veerasathpurush Allareddy
Resource Type: Book chapter
Publication Details: Machine Learning in Dentistry, pp.131-143
Publisher: Springer International Publishing; Cham
DOI: 10.1007/978-3-030-71881-7_11
Language: English
Date published: 07/25/2021
Academic Unit: Orthodontics
Record Identifier: 9984367580102771

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