Enhancing Early Diagnosis of Heart Diseases Using Convolutional Neural Networks (CNNs) (Asst. Lecturer Qusay Munir Diab)

  Share :          
  137

In line with global efforts to promote public health and leverage artificial intelligence for medical innovation, researchers are working on developing early diagnostic mechanisms for heart diseases using Convolutional Neural Networks, or CNNs. These models are inspired by the visual architecture of the human brain, which enables them to analyze complex medical images and detect subtle patterns that are often difficult to discern with the naked eye. CNNs are employed to process echocardiography, magnetic resonance imaging, and computed tomography scans, aiming to enhance the accuracy of detecting cardiac abnormalities. The outputs of these networks are integrated with patients’ clinical data to assess risk levels and enable timely therapeutic interventions. The convolutional layers of the network automatically extract important features and biomarkers from medical image databases, reducing the need for manual interpretation and increasing the speed and precision of diagnoses. Additionally, these intelligent diagnostic systems are integrated with Internet of Things devices and wearable technologies to continuously monitor patients’ conditions and provide early alerts to healthcare providers when necessary. The use of Convolutional Neural Networks in early heart disease diagnosis represents a strategic step toward precision medicine, contributing to lower mortality rates, improved treatment effectiveness, and reduced long-term healthcare costs. This approach also reflects the commitment of academic and research institutions to achieving the Sustainable Development Goals, particularly SDG 3, which focuses on good health and well-being, by developing advanced diagnostic tools that reduce the burden of heart disease and improve quality of life. It also supports SDG 9, which promotes industry, innovation, and infrastructure, through the integration of AI and modern medical technologies into healthcare systems. Furthermore, it contributes to SDG 17 by strengthening partnerships among universities, research centers, and medical technology companies to accelerate the practical implementation of these solutions. University of Al-Mustaqbal – The First University in Iraq
  الهدف الثالث(الصحة الجيدة والرفاه).