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ISSN 1004-9037
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Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
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      05 July-September 2023, Volume 38 Issue 4
    Article

    AN IMPROVED ARTIFICIAL INTELLIGENCE MACHINE LEARNING FRAMEWORK TO HANDLE HEALTHCARE APPLICATIONS
    Godugu Sabera1, Dara Maria Sudha2
    Journal of Data Acquisition and Processing, 2023, 38 (4): 2595-2604 . 

    Abstract

    Healthcare is critical to living a happy life. However, itis quite difficult to secure a doctor's consultation for every health issue. This chatbot may be used by regular humans in any sort of emergency case, where it can advise people on primary care before seeing a doctor, or it can sometimes work as a doctor for small and short- term health issues such as a cold, headache, and so on. Along with this chatbot, there will be assistance for those in need who seek immediate solutions The original intent of chatbots was purely for human entertainment. Providing high-quality, cost-effective healthcare to India's expanding population is one of the country's top priorities right now, but it faces significant obstacles. In general, it must be able to understand what the user is trying to do and act accordingly. An array of new features has greatly expanded chatbots' informal skills up to this point. In their research, they provide a method for creating a chatbot using a deep neural network. A multi-layered neural network is used to learn from and analyse the data. The uniqueness of the predicted model lies in the fact that the bots may be trained on any computer file that supports the user's goals and demands. The integration of text-to-speech conversion increases the product's user-friendliness significantly.

    Keyword

    Chatbot, Health Care, Deep neural network


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ISSN 1004-9037

         

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