This study aims to enhance the accuracy of heart failure prediction modeling a Kaggle dataset composed of five sets of data over 11 patient attributes. Multiple machine-learning approaches were utilized to understand the data and forecast the likelihood of heart failure in a medical database...
This study investigates the performance improvement of heart disease prediction models using machine learning and deep learning algorithms. Initially, we utilized the Heart Failure Prediction Dataset from Kaggle. After preprocessing to ensure data quality, three distinct feature engineering techniques were ...
Patients with heart failure and society as a whole would benefit from accurate, organized diagnostic services13. In order to do this, this study creates a novel method for performing heart disease prediction by utilizing an improved self-attention-based transformer network. Preprocessing the dataset i...
The present study examines the role of feature selection methods in optimizing machine learning algorithms for predicting heart disease. The Cleveland Heart disease dataset with sixteen feature selection techniques in three categories of filter, wrapper,
Svetlana ulianova Cardiovascular disease dataset Retrieved from https://www.kaggle.com/sulianova/cardiovascular-disease-dataset (2019, january 01) Google Scholar [8] C.B. Latha, S.C. Jeeva Improving the accuracy of prediction of heart disease risk based on ensemble classification techniques July 02...
[20]https://www.kaggle.com/johnsmith88/heart-disease-dataset [Accessed 02 June 2021]. [21]Azur MJ, Stuart EA, Frangakis C, Leaf PJ. (2011). Multiple imputation by chained equations: what is it and how does it work. Int J Methods Psychiatr Res 20(1): 40-49. ...
the Cleveland heart disease dataset S1 and Hungarian heart disease dataset (S2) are used, which are available online at the University of California Irvine (UCI) machine learning repository and UCI Kaggle repository, and various researchers have used it for conducting their research studies28,31,32...
The dataset generated and analyzed during the current study are available in the Kaggle repository, (https://www.kaggle.com/datasets/mohamedamineferrag/edgeiiotset-cyber-security-dataset-of-iot-iiot). The dataset analyzed during the current study is available from the corresponding author upon rea...
We did not find other published results on the same dataset (available from Kaggle) for comparison. However, similar approaches with other larger data sets (378,256 patients from UK family practices) yielded similar results [21]. Failure to obtain better results could be due to the low number...
The study utilized the "Heart Failure Prediction Dataset" acquired from Kaggle, which consisted of 11 prevalent variables such as age, blood pressure, and cholesterol levels. These findings indicate that the hybrid model has promise as a powerful tool for predicting heart disease.Hossain, Md. ...