Abstract
Presently, diagnosis of disease is an important issue in the field of health care using Artificial Intelligence (AI). Doctors are not always present and sometimes although doctors are available but people are not able to afford them due to financial issues. The basic information like blood pressure, ages, etc. are known at that moment without knowing any symptoms how the disease can be predicted. If people know the symptoms of how the disease can be predicted? Both of these aspects, we would look into, propose algorithms, and implement them for the welfare of the society. The proposed algorithms are capable of classifying diseases of people and healthy people in efficient manner. In this work, the authors also link the concepts of probability with fuzzy logic and describe how to interpret them. Then, we can consider human being as a kind of machine and we know that any machine can be described by a parameter called reliability but the definition of classical reliability if used in case of human being fails miserably. The aim of this paper is to make a bridge among fuzzy logic, probability, and reliability.
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Das, S., Sanyal, M.K., Datta, D. (2020). Artificial Intelligent Reliable Doctor (AIRDr.): Prospect of Disease Prediction Using Reliability. In: Mandal, J., Sinha, D. (eds) Intelligent Computing Paradigm: Recent Trends. Studies in Computational Intelligence, vol 784. Springer, Singapore. https://doi.org/10.1007/978-981-13-7334-3_3
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DOI: https://doi.org/10.1007/978-981-13-7334-3_3
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