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Heart disease prediction using machine learning techniques
| dc.contributor.advisor | Lawah, A. I. | |
| dc.contributor.author | Ali, A. A. | |
| dc.coverage.spatial | Гомель | ru_RU |
| dc.date.accessioned | 2025-05-30T05:54:26Z | |
| dc.date.available | 2025-05-30T05:54:26Z | |
| dc.date.issued | 2025 | |
| dc.identifier.citation | Ali, A. A. Heart disease prediction using machine learning techniques / A. A. Ali ; scientific supervisor A. I. Lawah // II Международный молодёжный научно-культурный форум студентов, магистрантов, аспирантов и молодых ученых : сборник материалов, Гомель, 22-24 января 2025 г. / Гомел. гос. техн. ун-т имени П. О. Сухого [Республика Беларусь], Таизский университет [Республика Йемен], Научная организация исследований и инноваций [Республика Йемен] ; под общ. ред. А. А. Бойко. – Гомель : ГГТУ им. П. О. Сухого, 2025. – C. 40. | ru_RU |
| dc.identifier.uri | https://elib.gstu.by/handle/220612/41674 | |
| dc.description.abstract | Heart disease is often called the silent killer, affecting millions without warning. Understanding how to predict and manage this condition is crucial for saving lives. the three key risk factors: high blood pressure, high cholesterol, and smoking. the urgency to identify these risks early cannot be overstated. The Urgency for Early Detection and Prevention Strategies Early detection can significantly reduce the chance of severe heart conditions. In this paper, we suggest an approach that uses machine learning techniques to identify important traits, increasing the precision of cardiovascular disease prediction. | ru_RU |
| dc.language.iso | en | ru_RU |
| dc.publisher | ГГТУ им. П.О. Сухого | ru_RU |
| dc.subject | Machine learning | ru_RU |
| dc.subject | Heart disease prediction | ru_RU |
| dc.subject | Health care | ru_RU |
| dc.title | Heart disease prediction using machine learning techniques | ru_RU |
| dc.type | Article | ru_RU |
