Figures for heart attack prediction using ML
<p dir="ltr">Heart attack prediction using machine learning involves analyzing biomarkers such as cholesterol levels, blood pressure, heart rate, glucose levels, and inflammatory markers like C-reactive protein to assess risk. Advanced algorithms, including logistic regression, decis...
محفوظ في:
| المؤلف الرئيسي: | |
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| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
إضافة وسم
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| الملخص: | <p dir="ltr">Heart attack prediction using machine learning involves analyzing biomarkers such as cholesterol levels, blood pressure, heart rate, glucose levels, and inflammatory markers like C-reactive protein to assess risk. Advanced algorithms, including logistic regression, decision trees, random forests, and deep learning models, process this data to identify patterns linked to heart attacks. These models are trained on labeled datasets, validated using techniques like cross-validation, and evaluated using metrics such as accuracy, precision, and recall. By integrating biomarker data with ML, healthcare professionals can achieve early detection and personalized risk assessment, enabling timely interventions and improved patient outcomes.</p> |
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