Survey on Asclepius: A User-Centric Chatbot Bridging the Gap in Healthcare Integrated with VPN Technology
This groundbreaking paper introduces Asclepius, a revolutionary software solution aimed at transforming early healthcare assistance through the seamless integration of cutting-edge technologies. At its core lies a sophisticated chatbot system, augmented with machine learning capabilities, facilitating swift and efficient connections between users and local medical professionals. With a strong emphasis on user anonymity and security, particularly concerning sensitive mental health concerns, Asclepius ensures utmost privacy throughout the interaction process. Constructed with meticulous attention to healthcare technology and security, Asclepius has been developed following extensive research across various domains, incorporating insights from acclaimed research articles to optimize and build an effective model. Central to its functionality is the utilization of state-of-the-art facial recognition technology and secure authentication protocols, instilling confidence in the system's reliability by enabling accurate user verification upon login. As of the publishing date, Asclepius has an 89% accuracy for its diagnoses by making use of a Supervised Decision tree-based Machine Learning Model. Through the incorporation of integrated virtual private network (VPN) technology, the project further establishes a secure communication channel between users and healthcare professionals, guaranteeing the protection of sensitive information and fostering a safe, confidential environment for seeking assistance. By seamlessly integrating a vast array of advanced technologies, Asclepius provides users with a comprehensive and user-friendly interface, prioritizing convenience and security in healthcare interactions and heralding a transformative shift in the landscape of early healthcare assistance.
Authors
- Vineet Kumar Awasthi (ORCID: https://orcid.org/0000-0003-3712-785X)
- Dolly Sharma (ORCID: https://orcid.org/0000-0002-7887-8708)
- Deepika Shekhawat (ORCID: https://orcid.org/0000-0002-6271-4602)
- A. Saranya
- Garima Shukla (ORCID: https://orcid.org/0000-0003-2954-1364)
- P. K. Shukla (ORCID: https://orcid.org/0009-0008-5354-8957)
Institutions
- Graphic Era University (IN)
Publication Details
- Published
- 2024-11-22
- DOI
- https://doi.org/10.1109/aece62803.2024.10911262
- Primary Topic
- FinTech, Crowdfunding, Digital Finance
- Type
- article
- Field-Weighted Citation Impact
- 0.00