Predictive Analysis of Cardiovascular Health Through Machine Learning.
Abstract & Details
Research Area
Computer Engineering
Keywords
Heart Disease Prediction
Machine Learning
Python
Data Preprocessing
Feature Engineering
Model Selection
Data Collection
Evaluation Metrics
Logistic Regression
Decision Trees
Random Forest
Support Vector
Machines (SVM)
Naive Bayes
K-Nearest Neighbors (KNN)
Ensemble Learning.
Abstract
The “Predictive Analysis of Cardiovascular Health Through Machine Learning” project ventures into the
critical realm of Healthcare. Just as financial markets endeavor to predict the future value of stocks, this
project aspires to preict something even more precious – the state of one’s cardiovascular health.
Leveraging the power of machine learning, this undertaking explores the intricate web of factors
influencing heart disease, aiming to offer early, accurate prediction and, consequently, lifesaving
insights.
The abstract heartbeats with the promise of a future where healthcare becomes increasingly proactive,
where personalized assessments can identify before they manifest. Much like the stock market’s
complexity, understanding the heart’s intricate dance with various variables presents formidable
challenges. Nevertheless, the otential rewards are equally great – the possibility of intervening in heart
disease, a leading cause of mortality worldwide.
This projects’s significance transcends the confines of algorithms and datasets; it embodies the
intersection of technology and human well-being, providing a compelling narrative of using advanced
data analytics and predictive modeling to save lives. Just as stock proce predictions hold the key to
finacials gains, here, we unlock the potential to predict and prevent cardiovascular ailments. The project
exemplifies the potency of technology to illuminate the path towards better health and longevity.
We also analyze the advantages and disadvantages of using machine learning in this context. By the end
of this presentation, you will gain insights into the potential of machine learning to revolutionize heart
disease diagnosis and contribute to better healthcare outcomes.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Takbhate T.K | MIT College Of Railway Engineering And Research, Barshi, Maharashtra, India, |
| 2 | Siddhant Amar Singh | MIT College Of Railway Engineering And Research, Barshi, Maharashtra, India |
| 3 | Rohit Prakash Gore | MIT College Of Railway Engineering And Research, Barshi, Maharashtra, India, |
| 4 | Aniket Anil Kshirsagar | MIT College Of Railway Engineering And Research, Barshi, Maharashtra, India, |
| 5 | Sumit Sanjay Bhosle | MIT College Of Railway Engineering And Research, Barshi, Maharashtra, India, |
How to Cite
Use the following formats to cite this article in your research.
APA Style
T.K, Takbhate, Singh, Siddhant Amar, Gore, Rohit Prakash, Kshirsagar, Aniket Anil, & Bhosle, Sumit Sanjay (2024). Predictive Analysis of Cardiovascular Health Through Machine Learning.. International Journal of Advance Research and Innovative Ideas In Education, 10(3), 375-384.
MLA Style
T.K, Takbhate, et al. "Predictive Analysis of Cardiovascular Health Through Machine Learning.." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, 2024, pp. 375-384.
IEEE Style
Takbhate T.K, Siddhant Amar Singh, Rohit Prakash Gore, Aniket Anil Kshirsagar, and Sumit Sanjay Bhosle, "Predictive Analysis of Cardiovascular Health Through Machine Learning.," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, pp. 375-384, 2024.
Vancouver Style
T.K Takbhate, Singh Siddhant Amar, Gore Rohit Prakash, Kshirsagar Aniket Anil, Bhosle Sumit Sanjay. Predictive Analysis of Cardiovascular Health Through Machine Learning.. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(3):375-384.
Harvard Style
T.K, Takbhate, Singh, Siddhant Amar, Gore, Rohit Prakash, Kshirsagar, Aniket Anil, & Bhosle, Sumit Sanjay (2024) 'Predictive Analysis of Cardiovascular Health Through Machine Learning.', International Journal of Advance Research and Innovative Ideas In Education, 10(3), pp. 375-384.
Chicago Style
T.K, Takbhate, et al. "Predictive Analysis of Cardiovascular Health Through Machine Learning.." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 375-384.
Turabian Style
T.K, Takbhate, et al. "Predictive Analysis of Cardiovascular Health Through Machine Learning.." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 375-384.
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