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Artificial Intelligence, Machine Learning and Reasoning in Health Informatics—An Overview

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Part of the Intelligent Systems Reference Library book series (ISRL,volume 192)

Abstract

As humans are intelligent, to mimic or models of human certain intelligent behavior to a computer or a machine is called Artificial Intelligence (AI). Learning is one of the activities by a human that helps to gain knowledge or skills by studying, practising, being taught, or experiencing something. Machine Learning (ML) is a field of AI that mimics human learning behavior by constructing a set of algorithms that can learn from data, i.e. it is a field of study that gives computers the ability to learn without being explicitly programmed. The reasoning is a set of processes that enable humans to provide a basis for judgment, making decisions, and prediction. Machine Reasoning (MR), is a part of AI evolution towards human-level intelligence or the ability to apply prior knowledge to new situations with adaptation and changes. This book chapter presents some AI, ML and MR techniques and approached those are widely used in health informatics domains. Here, the overview of each technique is discussed to show how they can be applied in the development of a decision support system.

Keywords

  • Artificial Intelligence
  • Machine learning
  • Reasoning
  • Fuzzy logic
  • Support Vector Machine (SVM)
  • Random Forest (RF)
  • Artificial Neural Network (ANN)
  • K-Nearest Neighbor (k-NN)
  • K-means clustering
  • Fuzzy C-means (FCM) Clustering
  • Case-Based Reasoning (CBR)

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Correspondence to Mobyen Uddin Ahmed .

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Ahmed, M.U., Barua, S., Begum, S. (2021). Artificial Intelligence, Machine Learning and Reasoning in Health Informatics—An Overview. In: Ahad, M.A.R., Ahmed, M.U. (eds) Signal Processing Techniques for Computational Health Informatics. Intelligent Systems Reference Library, vol 192. Springer, Cham. https://doi.org/10.1007/978-3-030-54932-9_7

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