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Paper ID:IJSREM68443

MEDBRIEF

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM68443

Volume:

10 |

10 |

Oct 2026

Pages:

1-11

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

SKB

Sanjay Krishna B

Department of Computer Science

Sri Shakthi Institute Of Engineering And Technology

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NKSA

Nikil Karthik S A

Department of Computer Science

Sri Shakthi Institute Of Engineering And Technology

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NSK

Nithiya Sri K

Department of Computer Science

Sri Shakthi Institute Of Engineering And Technology

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LR

Logesh R

Department of Computer Science

Sri Shakthi Institute Of Engineering And Technology

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ORS

Oviya Rethanya S

Department of Computer Science

Sri Shakthi Institute Of Engineering And Technology

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Mentors

SKB

Sanjay Krishna B

Department of Computer Science

Sri Shakthi Institute Of Engineering And Technology

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Abstract

A kiosk interface registers or looks up patients, records consent, collects medical reports and supports English and Tamil interaction. A separate doctor portal provides a review queue, source-linked draft summaries, emergency red-flag alerts and physician attestation. Each extracted field shows its source, confidence and verification state; unreadable content is labelled and directed to the original document. AI output remains a draft and the physician retains final authority. React, Vite, TypeScript, Node.js, Prisma and PostgreSQL support the application, with OCR and local language-model adapters. An audit reports 301 passing tests in 25 files and successful builds for all three workspaces. The same audit finds a disconnected database, unpersisted upload binaries, an unregistered document route and template-based OCR. These results do not establish clinical accuracy or deployment readiness.

KEYWORDS

clinical decision support optical character recognition grounded summarization emergency red flags consent management physician review audit logging kiosk accessibility.

Cite This Article

Sanjay Krishna B, Nikil Karthik S A, Nithiya Sri K, Logesh R, Oviya Rethanya S, Sanjay Krishna B, "MEDBRIEF," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 10, pp. 1-11, Oct 2026.

Full Article/Conclusion

MEDBRIEF implements an AI-assisted healthcare document management and clinical support prototype that connects kiosk registration, consent, document upload, extraction, draft summarization, emergency alerts and physician review. Its principal objective is not simply to generate a summary, but to make the basis and limits of each clinical field inspectable. Readable fields display source, confidence and verification state, and unreadable inputs retain explicit uncertainty and direct the physician to the original document. The reported tests and builds demonstrate concrete implementation behaviour, but the integration audit shows that passing tests do not prove reliable operation. The database was disconnected, uploaded files were not persisted, the document viewer route was incomplete and OCR remained template-based. MEDBRIEF therefore remains an assistive prototype with synthetic data, and clinical responsibility remains with the treating physician. The integrated Registration to Consent to Document to Summary to Physician Review workflow is the project's strongest practical feature. Its completion depends on resolving persistence, storage, retrieval and OCR before further interface work. Further evaluation should extend this workflow to consented real documents and carefully measured hospital pilots.

References

[1]   P. Lewis et al. Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. Advances in Neural Information Processing Systems, 33, 2020, pp. 9459-9474. https://arxiv.org/abs/2005.11401 [2]   Z. Ji et al. Survey of Hallucination in Natural Language Generation. ACM Computing Surveys, 55(12), 2023, Article 248. https://doi.org/10.1145/3571730 [3]   N. Provos and D. Mazieres. A Future-Adaptable Password Scheme. USENIX Annual Technical Conference, 1999, pp. 81-91. [4]   Tesseract OCR contributors. Tesseract User Manual. Official documentation.https://tesseract-ocr.github.io/tessdoc/ [5]   Microsoft. Document layout analysis with Document Intelligence. Official documentation. https://learn.microso ft.com/en-us/azure/ai-services/document-intelligence/preb uilt/layout [6]   Prisma. Prisma ORM Documentation. Official database toolkit documentation. https://www.prisma.io/docs [7]   PostgreSQL Global Development Group. PostgreSQL 16 Documentation. Official database documentation. https://www.postgresql.org/docs/16/ [8]   OpenAI. API Reference. Official documentation for the chat completions interface used by OpenAI-compatible adapters. https://platform.openai.com/docs/api-reference [9]   Meta Open Source. React Documentation. Official web library documentation. https://react.dev [10]   Vite contributors. Vite Guide. Official build tool documentation. https://vite.dev/guide/

Editorial & Review Transparency

Publication Date

10/28/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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Conflict of Interest

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

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