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Stream/Area:
-
Subject:
-
Paper ID:
IJSREMWP9
Volume:
9 |
6 |
Jun 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
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.
With the advancement in AI, early detection of health issues through textual analysis of medical reports has become viable. This paper presents an AI-based solution that analyzes unstructured medical text using Natural Language Processing (NLP) to detect conditions like infections, chronic illnesses, and more. The system is deployed as a Flask web application allowing users to upload reports and receive instant diagnostic feedback. The engine leverages custom Python logic without cloud APIs, ensuring offline accessibility. The results show consistent and useful outputs for various real-world inputs.
KEYWORDS
Publication Date
6/29/2025
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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No funding information available for this research.
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