Brain Stroke Prediction Using Machine Learning & Python Flask

Authors

  • Sachin Verma Chhavi Kumbhalkar, Pranjal Giradkar , Ritisha Bansod Department Of Computer Science & Engineering, KDK College Of Engineering, Nagpur Author
  • Misha Thakre Chhavi Kumbhalkar, Pranjal Giradkar , Ritisha Bansod Department Of Computer Science & Engineering, KDK College Of Engineering, Nagpur Author
  • Chandrashekhar Tidake Chhavi Kumbhalkar, Pranjal Giradkar , Ritisha Bansod Department Of Computer Science & Engineering, KDK College Of Engineering, Nagpur Author
  • Nayana Yembarwar Chhavi Kumbhalkar, Pranjal Giradkar , Ritisha Bansod Department Of Computer Science & Engineering, KDK College Of Engineering, Nagpur Author
  • Aadinath Mundhe Chhavi Kumbhalkar, Pranjal Giradkar , Ritisha Bansod Department Of Computer Science & Engineering, KDK College Of Engineering, Nagpur Author
  • Ganesh Taynak Chhavi Kumbhalkar, Pranjal Giradkar , Ritisha Bansod Department Of Computer Science & Engineering, KDK College Of Engineering, Nagpur Author

Keywords:

Stroke Prediction, Cerebrovascular accident (CVA), Machine Learning Model, Brain Blood Supply

Abstract

A stroke (cerebrovascular accident, CVA) happens when part of the brain doesn’t get enough blood, causing loss of function in the affected area. It can be ischemic (due to blocked blood flow) or hemorrhagic (caused by bleeding in the brain). Stroke is a medical emergency that can lead to death or permanent disability, and ischemic strokes need immediate treatment within hours.

A mini-stroke (transient ischemic attack, TIA) causes temporary symptoms that go away within 24 hours but still requires urgent medical care to prevent future strokes. According to the WHO, stroke is the third leading cause of death worldwide, responsible for 10.7% of total deaths. Our machine learning (ML) model predicts stroke risk based on key factors such as age, gender, glucose level, blood pressure, married or unmarried and smoking status, focusing on major stroke risk factors.

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References

8.1 Research Papers & Journals

• WHO Stroke Report (2022) – World Health Organization, Available at: www.who.int

• M. Gupta & A. Sharma (2021) – "Predicting Stroke Risk Factors Using AI-Based Models" (IEEE Access).

• K. Das, et al. (2020) – "Stroke Prediction Using Machine Learning Algorithms" (International Journal of Healthcare Informatics).

• Manisha Sirsat, Eduardo Ferme, Joana Camara, “Machine Learning for Brain Stroke: A Review,”.

• Harish Kamal, Victor Lopez, Sunil A. Sheth, “Machine Learning in Acute Ischemic Stroke Neuroimaging,”.

8.2 Websites

• Flask Documentation - Lightweight

• IEEE Xplore Digital Library

• Kaggle Datasets - Open datasets for stroke prediction.

• Scikit-learn Documentation - Machine learning tools and techniques used in the project.

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Published

30-06-2025

Issue

Vol. 16 No. 1 (2025): Special Edition : SPARK 2025

Section

Original Research Articles

License

Copyright (c) 2025 International Journal for Research Publication and Seminar

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

How to Cite

Brain Stroke Prediction Using Machine Learning & Python Flask. (2025). International Journal for Research Publication and Seminar, 16(1), 1145-1151. https://jrpsjournal.in/index.php/j/article/view/252

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