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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM41785

Leveraging AI-Driven Virtual Assistant for Enhancing Patient

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM41785

Volume:

9 |

2 |

Feb 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM41785

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

1D

1]Ashwini Dake

[G

[2]Atharva Ghadge

[K

[3]Shwet Khairnar

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Abstract

The AI Assist For Patient is a comprehensive healthcare assistant designed to meet evolving patient needs by combining advanced AI with user-centered features. The app offers AI-driven symptom detection, helping users understand health concerns, and facilitates appointment scheduling with nearby doctors for convenient care. Blockchain technology secures medical records, safeguarding sensitive information with robust data security. Additional features like real-time health reports and facial recognition enhance personalized experiences, while machine learning refines patient satisfaction metrics, making it a responsive and adaptable solution. The user-friendly interface, developed with React Native and Figma, emphasizes ease of use, and a scalable backend in SQL or MongoDB supports secure data storage and quick access. Overall, AI Assist For Patient stands out as an innovative, secure, and efficient virtual assistant, empowering patients to manage their health confidently

KEYWORDS

AI healthcare assistant Symptom detection Appointment scheduling Medical record storage Machine learning in healthcare Secure patient data

Cite This Article

1]Ashwini Dake, [2]Atharva Ghadge, [3]Shwet Khairnar, "Leveraging AI-Driven Virtual Assistant for Enhancing Patient," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 2, Feb 2025. https://doi.org/10.55041/IJSREM41785

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Publication Date

2/23/2025

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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