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In the context of Industry 4.0 becoming a development priority in many fields, artificial intelligence (AI) has emerged as a promising trend in healthcare. This chapter builds on previous research and combines experiments on various datasets to propose a simple yet highly effective deep learning model for disease diagnosis via X-ray images. The model is implemented on a website that can be accessed remotely. This approach has the potential to reduce examination and screening time, minimize errors, and enable convenient remote implementation. Experimental results indicate that the proposed model has been tested for demonstration in this method’s effectiveness at 95%. Consequently, it can save time, costs, and resources, while mitigating the limitations of traditional methods.

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Teachable Machine Model Combining Machine Learning and Deep Learning for Disease Diagnosis

  • 会议论文

  • 发表日期：

    2025年

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  • Quoc Hung Nguyen,
  • Xuan Huy BUI

摘要

In the context of Industry 4.0 becoming a development priority in many fields, artificial intelligence (AI) has emerged as a promising trend in healthcare. This chapter builds on previous research and combines experiments on various datasets to propose a simple yet highly effective deep learning model for disease diagnosis via X-ray images. The model is implemented on a website that can be accessed remotely. This approach has the potential to reduce examination and screening time, minimize errors, and enable convenient remote implementation. Experimental results indicate that the proposed model has been tested for demonstration in this method’s effectiveness at 95%. Consequently, it can save time, costs, and resources, while mitigating the limitations of traditional methods.