A Novel Cluster And Rank Based Method For Prediction Of Heart Diseases
- Indbinding:
- Paperback
- Sideantal:
- 112
- Udgivet:
- 25. marts 2023
- Størrelse:
- 152x7x229 mm.
- Vægt:
- 175 g.
- 8-11 hverdage.
- 7. december 2024
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- 1 valgfrit digitalt ugeblad
- 20 timers lytning og læsning
- Adgang til 70.000+ titler
- Ingen binding
Abonnementet koster 75 kr./md.
Ingen binding og kan opsiges når som helst.
Beskrivelse af A Novel Cluster And Rank Based Method For Prediction Of Heart Diseases
Heart disease is a leading cause of death worldwide, and early prediction is crucial for effective prevention and management. A novel cluster and rank-based method for prediction of heart disease involves using machine learning algorithms to cluster patients based on similar risk factors and rank them based on their likelihood of developing cardiovascular disease.
This method utilizes feature selection techniques to identify the most important risk factors and uses a classification model to predict the risk of heart disease based on these factors. The accuracy of the model is evaluated using metrics such as sensitivity, specificity, and AUC.
This approach has several advantages, including improved accuracy in predicting heart disease risk, the ability to identify subgroups of patients with similar risk profiles, and the potential to integrate data from electronic health records and other sources.
This method utilizes feature selection techniques to identify the most important risk factors and uses a classification model to predict the risk of heart disease based on these factors. The accuracy of the model is evaluated using metrics such as sensitivity, specificity, and AUC.
This approach has several advantages, including improved accuracy in predicting heart disease risk, the ability to identify subgroups of patients with similar risk profiles, and the potential to integrate data from electronic health records and other sources.
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