Welcome to my Data Mining course project presentation! I’m Resy Kumala Sari, a student at the Department of Industrial Engineering and Management at Yuan Ze University, Taiwan. In this video, I will delve into two significant studies that explore the application of neural networks in the management of hypertension, a major public health concern.
🔍 Study Overview:
Paper 1 Review: “Hypertension Diagnosis with Backpropagation Neural Networks for Sustainability in Public Health” by Orozco Torres et al. (2022). This study focuses on employing backpropagation neural networks to diagnose hypertension, underlining the importance of sustainable health practices.
Paper 2 Review: “Application of a backpropagation neural network model optimized by a particle swarm algorithm in predicting the risk of hypertension” by Yan et al. (2022). This research advances the method by integrating a particle swarm optimization algorithm, enhancing the predictive accuracy for hypertension.
🎯 Key Points:
The significance of improving hypertension diagnosis and prediction using advanced neural network technologies.
Comparative insights into the methodologies and outcomes of both studies.
Implications of these technologies for future public health strategies.
đź’ˇ What You’ll Learn:
How neural networks can transform the diagnosis and prediction of health conditions like hypertension.
The potential of integrating sophisticated algorithms such as particle swarm optimization to increase the effectiveness of these models.
The impact of technological advancements on public health sustainability.
🤝 Join the Discussion:
I look forward to your thoughts and questions in the comments below! Let’s discuss how these technologies could shape the future of healthcare.
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Thank you for watching, and enjoy the presentation!
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