A Literature Survey on BIO-PULSE AI based Medcare App

Author:

Nawaz Shariff B 1,S H Gavisiddesh 1,Prof. Indushree M 1

Affiliation:

1. Global Academy of Technology, Bengaluru, Karnataka, India

Abstract

The MedCare Chatbot signifies a significant leap forward in healthcare technology, providing users with individualized medical guidance and prescription suggestions. Going beyond its primary functions, this inventive chatbot incorporates a pioneering feature centered on the identification of skin diseases through image processing techniques. Utilizing the capabilities of artificial intelligence and computer vision, the MedCare Chatbot can analyse images of skin conditions submitted by users, furnishing precise diagnoses and treatment recommendations. This paper details the design, implementation, and assessment of this advanced functionality seamlessly integrated into the MedCare Chatbot. Employing a dual strategy of symptom-based prescription advice and image-based skin disease detection, the MedCare Chatbot aims to enhance healthcare accessibility and empower users to actively manage their well-being

Publisher

Naksh Solutions

Reference16 articles.

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3. [3] R. Katarya and P. Srinivas, "Predicting Heart Disease at Early Stages using Machine Learning: A Survey," 2020 International Conference on Electronics and Sustainable Communication Systems (ICESC), Coimbatore, India, 2020, pp. 302-305, doi: 10.1109/ICESC48915.2020.9155586

4. [4] N. Rajeswari, S. Nachammai, P. E. Jemima and A. M. Rajeswari, "Unexpected Health Issues Prediction In Medical Data Using Apriori Rare Based Outlier Detection Method," 2019 International Conference on Vision Towards Emerging Trends in Communication and Networking (ViTECoN), Vellore, India, 2019, pp. 1-6, doi: 10.1109/ViTECoN.2019.8899573

5. [5]N. C. F. Codella et al., "Segmentation of Both Diseased and Healthy Skin From Clinical Photographs in a Primary Care Setting," 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Honolulu, HI, USA, 2018, pp. 3414-3417, doi: 10.1109/EMBC.2018.8512980.

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