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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM65082

AI-POWERED HEALTHCARE APPOINTMENT ASSISTANCE SYSTEM MEDEASE

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM65082

Volume:

10 |

6 |

Jun 2026

Pages:

1-5

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

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

JC

Jayesh Chaudhari

Department of Information Technology

Sinhgad Institute of Technology and Science, Pune

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TB

Tanishka Bachhav

Department of Information Technology

Sinhgad Institute of Technology and Science, Pune

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AG

Aastha Ghorpade

Department of Information Technology

Sinhgad Institute of Technology and Science, Pune

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AG

Akshata Garje

Department of Information Technology

Sinhgad Institute of Technology and Science, Pune

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SP

Snehal Pohakar

Department of Information Technology

Sinhgad Institute of Technology and Science, Pune

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Mentors

SNF

Swati N. Firame

Department of Information Technology

Sinhgad Institute of Technology and Science, Pune

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Abstract

The rapid growth of digital healthcare services has created a strong need for intelligent and user-friendly systems that improve patient accessibility and emergency responsiveness. This research presents MedEase, an AI-powered healthcare appointment and assistance platform designed to simplify doctor appointment scheduling while integrating advanced healthcare support features into a single mobile application. The pro-posed system enables patients to book, reschedule, and manage appointments efficiently, reducing waiting time and improving communication with healthcare providers. To enhance medication safety, the platform incorporates an OCR-based prescription scanning module that extracts medicine details from handwritten or printed prescriptions and stores them as digital records for future access. An SOS emergency alert feature is also integrated to provide instant support during critical medical situations by sharing real-time user location with emergency contacts or nearby ambulance services. In addition, the application includes a health awareness video section that delivers verified short healthcare content to promote preventive care and improve patient awareness. The system is implemented using Flutter, Firebase, and AI-based OCR techniques, ensuring secure cloud storage, fast real-time synchronization, and smooth user interaction. By combining appointment management, prescription digitization, emergency response, and healthcare education into one unified platform, MedEase offers a scalable and practical solution for modern healthcare challenges. The proposed approach improves service efficiency, reduces manual dependency, and contributes toward accessible, technology-driven patient care.

KEYWORDS

Artificial Intelligence Healthcare Appointment System OCR Prescription Scanner Emergency SOS Flutter Firebase Digital Healthcare Patient Care Medical Assistance Real-time Location Tracking Cloud Integration

Cite This Article

Jayesh Chaudhari, Tanishka Bachhav, Aastha Ghorpade, Akshata Garje, Snehal Pohakar, Swati N. Firame, "AI-POWERED HEALTHCARE APPOINTMENT ASSISTANCE SYSTEM MEDEASE," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-5, Jun 2026.

Full Article/Conclusion

This paper presented MedEase, an AI-powered healthcare appointment and assistance system that integrates doctor ap-ointment booking, OCR-based prescription scanning, SOS emergency support, and verified health awareness content into a single mobile platform. The proposed system improves healthcare accessibility, reduces waiting time, simplifies pre-scription understanding, and enhances emergency responsive-ness. By combining cloud-based storage, real-time notifications, and AI-driven OCR techniques, the platform offers a secure, scalable, and patient-friendly healthcare solution. Overall, MedEase provides an effective step toward smarter, faster, and more accessible digital healthcare services.

References

[1]     G. Eason, B. Noble, and I. N. Sneddon, “On certain integrals of Lipschitz-Hankel type involving products of Bessel functions,” Phil. Trans. Roy. Soc. London, vol. A247, pp. 529–551, April 1955. [2]     J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892, pp.68–73. [3]     I. S. Jacobs and C. P. Bean, “Fine particles, thin films and exchange anisotropy,” in Magnetism, vol. III, G. T. Rado and H. Suhl, Eds. New York: Academic, 1963, pp. 271–350. [4]     K. Elissa, “Title of paper if known,” unpublished. [5]     R. Nicole, “Title of paper with only first word capitalized,” J. Name Stand. Abbrev., in press. [6]     Y. Yorozu, M. Hirano, K. Oka, and Y. Tagawa, “Electron spectroscopy studies on magneto-optical media and plastic substrate interface,” IEEE Transl. J. Magn. Japan, vol. 2, pp. 740–741, August 1987 [Digests 9th Annual Conf. Magnetics Japan, p. 301, 1982]. [7]     M. Young, The Technical Writer’s Handbook. Mill Valley, CA: Univer-sity Science, 1989.

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Publication Date

6/16/2026

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Double-Blind Peer Review

Review Rounds: 2

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