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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM49642

BRAIN STROKE PREDICTION AND DETECTION AND DIAGNOSIS

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM49642

Volume:

9 |

6 |

Jun 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/ijsrem49642

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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SYD

Shreya Y D

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Abstract

– Stroke is one of the leading causes of death and disability worldwide. Early diagnosis and risk assessment can help significantly reduce fatalities and improve patient outcomes. This project proposes an integrated web-based system for stroke prediction, detection, and diagnosis. It uses a machine learning model (Random Forest) for structured health data and a CNN model for detecting stroke from CT/MRI scan images. The system also provides health suggestions based on key risk indicators. This paper presents the concept and design, which will be fully implemented and validated in the final stage.

KEYWORDS

Stroke prediction machine learning CNN CT scan MRI diagnosis system Flask

Cite This Article

Shreya Y D, "BRAIN STROKE PREDICTION AND DETECTION AND DIAGNOSIS," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 6, Jun 2025. https://doi.org/10.55041/ijsrem49642

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Publication Date

6/7/2025

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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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