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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14

Issue per Year : 12

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Paper Title: Blood Pressure Expert System
Authors Name: Akash Kumar , Radhikesh Mishra , Abhisekh , Mayank Dayal
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IJRTI_202653
Published Paper Id: IJRTI2505047
Published In: Volume 10 Issue 5, May-2025
DOI:
Abstract: This research presents BPES, a cardiovascular risk assessment system utilizing interpretative machine learning. The model combines Principal Component Analysis (PCA) with Logistic Regression to enhance predictive accuracy while preserving interpretability. A Flask API back-end with a ReactJS front-end enables real-time interaction. BPES integrates American Heart Association (AHA) guidelines for rule-based hypertension classification. The system supports clinical insight through interactive visualizations such as ROC curves, confusion matrices, feature importance plots, and PCA scatter plots. Designed for both clinical and web-based use, BPES demonstrates a robust, explainable AI framework tailored to provide real-time, data-driven support for healthcare professionals and patients.
Keywords: Cardiovascular disease, Expert System, Hypertension, Logistic Regression, Machine Learning, PCA, Real-time prediction
Cite Article: "Blood Pressure Expert System", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 5, page no.a452-a462, May-2025, Available :http://www.ijrti.org/papers/IJRTI2505047.pdf
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ISSN: 2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publication Details: Published Paper ID: IJRTI2505047
Registration ID:202653
Published In: Volume 10 Issue 5, May-2025
DOI (Digital Object Identifier):
Page No: a452-a462
Country: Ghaziabad, Uttar Pradesh, India
Research Area: Computer Engineering 
Publisher : IJ Publication
Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2505047
Published Paper PDF: https://www.ijrti.org/papers/IJRTI2505047
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED, Journal Starting Year (ESTD) : 2016

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