AI Based Treatment Guidance for Heart Disease Patients Based on Deep Learning Techniques
Keywords:
AI-based treatment, heart disease, deep learning, convolutional neural networks (CNNs), recurrent neural networks (RNNs), personalized medicineAbstract
Heart disease remains a leading cause of mortality worldwide, necessitating innovative approaches for effective diagnosis and treatment. This research paper explores the development of an AI-based treatment guidance system for heart disease patients, leveraging deep learning techniques to enhance accuracy and personalization in medical care. The proposed system integrates various deep learning models, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), to analyse patient data such as medical histories, diagnostic test results, and lifestyle factors. By processing and learning from this data, the system provides tailored treatment recommendations and predicts potential outcomes, aiming to support healthcare professionals in making informed decisions. The effectiveness of the system is validated through extensive experiments and comparisons with traditional treatment methods. Results demonstrate significant improvements in treatment accuracy and patient outcomes, highlighting the potential of deep learning in transforming heart disease management.
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