Medical technology is advancing rapidly, allowing doctors to predict and diagnose diseases more accurately than ever before. This paper introduces a smart medical prediction system that combines two powerful artificial intelligence (AI) techniques: deep learning for analysing medical images and traditional data processing for handling text and numerical information. Keywords: - Natural Language Processing (NLP), CNN, Image classification, Text VectorizationThis approach can be expanded to different medical fields, such as cardiology, neurology, and oncology. Additionally, exploring other deep learning models may further improve accuracy and efficiency.The versatility of this approach allows it to be applied across various medical fields, including cardiology, neurology, and oncology, where accurate diagnosis is critical for early intervention and treatment planning. Furthermore, as AI models continue to evolve, exploring more advanced deep learning architectures could further enhance the system’s predictive accuracy and efficiency.By combining deep learning with traditional medical analysis, this hybrid system is a major breakthrough in predicting diseases. It helps doctors work more efficiently by organizing and analyzing medical data, making it easier to diagnose patients accurately.This system can speed up decision-making, reduce errors, and support doctors in providing better treatment. As a result, patients receive faster and more accurate care, leading to better health outcomes.This innovation is an important step toward using smart technology in healthcare, making medical diagnosis more reliable and improving the future of medicine.
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