A Smart Healthcare Application using Artificial Intelligence (AI) and Machine Learning (ML)

The combination of Artificial Intelligence and Machine Learning technologies within the healthcare industry has enabled a significant shift in conventional methodologies, offering more opportunities to enhance the patient care, streamline resource management, and optimize healthcare delivery efficie...

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Published in2024 5th International Conference on Image Processing and Capsule Networks (ICIPCN) pp. 204 - 210
Main Authors Umbare, Rupali, Patil, Ritesh, Mukund, Tejas, Rathod, Adesh, Rajurkar, Pratik
Format Conference Proceeding
LanguageEnglish
Published IEEE 03.07.2024
Subjects
Accuracy
AIgenerated descriptions
Algorithm selection
Chatbot
Deep learning
Google Dialog flow
Healthcare accessibility
Image processing
Industries
Intelligent healthcare
KNN
Machine learning algorithms
Medical services
NLP
Performance evaluation
Personalized medical assistance
Prediction algorithms
Reviews
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DOI10.1109/ICIPCN63822.2024.00041

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Summary:The combination of Artificial Intelligence and Machine Learning technologies within the healthcare industry has enabled a significant shift in conventional methodologies, offering more opportunities to enhance the patient care, streamline resource management, and optimize healthcare delivery efficiency. This research study describes a proposed system that uses AI and ML algorithms to previously available datasets to provide medical prescriptions and disease prediction based on the symptoms provided by the user. Proposed technique also integrates state-of-the-art AI technology, including Natural Language Processing (NLP) and Deep Learning (DL) to enable the chatbot to provide contextually appropriate descriptions of medical conditions and treatments. Extensive algorithm selection guarantees response generation accuracy, while the deployment is streamlined by establishing a connection with Google Dialogflow. When taken as a whole, these components improve healthcare accessibility. Performance review verifies that this approach is effective in addressing inquiries with accurate and helpful information. The proposed system holds significant potential for enhancing healthcare accessibility and efficiency, with opportunities for further research and collaboration with healthcare providers.
DOI:10.1109/ICIPCN63822.2024.00041