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

S. Sasikala, S. J. Subhashini, P. Alli, J. Jane Rubel Angelina
Copyright: © 2021 |Pages: 31
DOI: 10.4018/978-1-7998-5071-7.ch008
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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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Artificial Intelligence

Artificial Intelligence consists of two words Artificial and Intelligence, where Artificial defines “man-made” and Intelligence defines “thinking power,” therefore AI means “man-made thinking power.” Artificial Intelligence exists when a machine can have human-based skills such as learning, reasoning, and problem-solving. Holding an Artificial Intelligence is known to be a computer with the ability to perform cognitive functions such as perceiving, understanding, thinking and solving problems. With the aid of AI, software or devices that can solve real-world problems quite easily and accurately such as health issues, marketing, traffic problems etc. can be build. AI paves the way for other new technologies, for new devices.

Goals of Artificial Intelligence

The following goals are influenced by Artificial Intelligence in various fields. They include

  • 1.

    Replicate human intelligence

  • 2.

    Solve Knowledge-intensive tasks

  • 3.

    An intelligent connection of perception and action

  • 4.

    Building a machine which can perform tasks that requires human intelligence such as:

    • a.

      Proving a theorem

    • b.

      Playing chess

    • c.

      Plan some surgical operation

    • d.

      Driving a car in traffic

  • 5.

    Creating some system which can exhibit intelligent behavior, learn new things by itself, demonstrate, explain, and can advise to its user.

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