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Deep Learning Applications in Medical Imaging: Artificial Intelligence, Machine Learning, and Deep Learning

Deep Learning Applications in Medical Imaging: Artificial Intelligence, Machine Learning, and Deep Learning
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Author(s): S. Sasikala (Velammal College of Engineering and Technology, India), S. J. Subhashini (Velammal College of Engineering and Technology, India), P. Alli (Velammal College of Engineering and Technology, India)and J. Jane Rubel Angelina (Thiagarajar College of Engineering, India)
Copyright: 2021
Pages: 31
Source title: Deep Learning Applications in Medical Imaging
Source Author(s)/Editor(s): Sanjay Saxena (International Institute of Information Technology, India)and Sudip Paul (North-Eastern Hill University, India)
DOI: 10.4018/978-1-7998-5071-7.ch008

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Abstract

Machine learning is a technique of parsing data, learning from that data, and then applying what has been learned to make informed decisions. Deep learning is actually a subset of machine learning. It technically is machine learning and functions in the same way, but it has different capabilities. The main difference between deep and machine learning is, machine learning models become well progressively, but the model still needs some guidance. If a machine learning model returns an inaccurate prediction, then the programmer needs to fix that problem explicitly, but in the case of deep learning, the model does it by itself. Automatic car driving system is a good example of deep learning. On other hand, Artificial Intelligence is a different thing from machine learning and deep learning. Deep learning and machine learning both are the subsets of AI.

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