Artificial Intelligence Diagnosis: Fundamentals and Applications
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Diagnosis is an area of artificial intelligence that focuses on the development of algorithms and methods that are capable of determining whether or not the behavior of a system is appropriate. In the event that the system is not operating as it should, the algorithm should be able to identify, with as much precision as is feasible, the component of the system is malfunctioning as well as the nature of the problem that it is experiencing. The computation is founded on observations, which supply information on the behavior that is now taking place.
How You Will Benefit
(I) Insights, and validations about the following topics:
Chapter 1: Diagnosis (artificial intelligence)
Chapter 2: Inductive logic programming
Chapter 3: Machine learning
Chapter 4: Intelligent agent
Chapter 5: Artificial intelligence in healthcare
Chapter 6: Symbolic artificial intelligence
Chapter 7: Internist-I
Chapter 8: Model-based reasoning
Chapter 9: Partially observable Markov decision process
Chapter 10: Fault detection and isolation
(II) Answering the public top questions about artificial intelligence diagnosis.
(III) Real world examples for the usage of artificial intelligence diagnosis in many fields.
(IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of artificial intelligence diagnosis' technologies.
Who This Book Is For
Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of artificial intelligence diagnosis.
