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AISLDr: Artificial Intelligent Self-learning Doctor

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 695))

Abstract

In recent decades, observation is that there are numerous corruptions in medical diagnosis; instead of proper diagnosis, some corrupted practitioners follow the money-earning-diagnosis-path by trapping the patient at critical stage in some countries. The common people are suffering from lack of diagnosis due to high diagnostic cost and lack of certified practitioners. This paper analyzes this shortcoming and ‘design and implement’ an intelligent system (AISLDr) which can perform the same without any corruption in a cost effective manner as like honest human doctor. In this work, the disease Tuberculosis has taken as a prototype because many people of our country are suffering from this disease and they know it at critical stage as India is highest Tuberculosis (TB) burden country. Here, our AISLDr performs diagnosis as well as draws awareness in the society to serve the nation in sustainable manner using fuzzy logic, probabilistic reasoning, and artificial intelligence (AI).

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Correspondence to Sumit Das .

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Das, S., Sanyal, M., Datta, D., Biswas, A. (2018). AISLDr: Artificial Intelligent Self-learning Doctor. In: Bhateja, V., Coello Coello, C., Satapathy, S., Pattnaik, P. (eds) Intelligent Engineering Informatics. Advances in Intelligent Systems and Computing, vol 695. Springer, Singapore. https://doi.org/10.1007/978-981-10-7566-7_9

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  • DOI: https://doi.org/10.1007/978-981-10-7566-7_9

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7565-0

  • Online ISBN: 978-981-10-7566-7

  • eBook Packages: EngineeringEngineering (R0)

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