PREDICTIVE MODELS IN MACHINE LEARNING FOR CARDIOVASCULAR DISEASE

Registration ID: IJNRD_225069

Published ID: IJNRD2407268

DOI: Click Here to Get

Prathibha A E , Sanjana S , Prajwal K , Rishikesh C

Cardiovascular Disease, Machine Learning, ML and DL, Data set, Data Mining, Algorithms, Random Forest.

Cardiovascular diseases (CVDs) continue to pose significant challenges in healthcare, being a leading cause of mortality worldwide. The complexity of predicting CVDs necessitates advanced expertise and tools due to the wealth of available data in healthcare systems. However, the current healthcare landscape often lacks the requisite analysis tools to uncover crucial relationships and patterns within this data. In response, This study investigates the capabilities of machine learning (ML) and deep learning (DL) techniques in predicting cardiovascular disease (CVD). Highlighting ML's capacity to unearth new genotypes, phenotypes, and risk factors, as well as its ability to model intricate relationships, this paper underscores its role in advancing CVD prediction. Additionally, it delves into the contributions of DL techniques, particularly convolutional neural networks (CNNs), in augmenting medical image recognition, diagnosis, prediction, and assessment. Moreover, the paper discusses the advantages of stacked fusion models, which amalgamate various models' strengths to achieve heightened performance levels. Ultimately, this research suggests leveraging both ML and DL in conjunction to improve the precision of CVD prediction, advance preventive measures, and effectively identify individuals at high risk for cardiovascular diseases.

Published Paper   E-Certificate

Prathibha A E , Sanjana S, Prajwal K, & Rishikesh C (July-2024). PREDICTIVE MODELS IN MACHINE LEARNING FOR CARDIOVASCULAR DISEASE. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(7), c681-c687. https://ijnrd.org/papers/IJNRD2407268.pdf

Volume 9 Issue 7, July-2024

Pages : c681-c687

Paper Reg. ID: IJNRD_225069

Published Paper Id: IJNRD2407268

Downloads: 000121975

Research Area: Computer Engineering 

Country: Bangalore , Karnataka , India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2407268.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2407268

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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