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By seamlessly integrating a user-friendly interface, our solution is designed to facilitate the diagnosis of diabetic foot ulcers. Our deep learning model seamlessly categorizes diabetic foot ulcers based on their severity, using CNN and MobileNet integrated with Kotlin for Android. Users receive prompt insights, and users are reminded of the urgency of seeking medical treatment in critical cases by timely notifications. Through the implementation of cutting-edge technology, this combination of proactive healthcare management and image identification represents a significant advancement in the early detection of diabetic foot ulcers and has the potential to enhance patient outcomes.

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Innovative Methods Toward the Real-Time Detection of Ulcers in Diabetic Feet

  • 会议论文

  • 发表日期：

    2025年

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  • Cheruku Poorna Venkata Srinivasa Rao,
  • Kodhamala Swarna,
  • Shaik Asif Basha,
  • Thopula Nikitha,
  • Pagadala Komali

摘要

By seamlessly integrating a user-friendly interface, our solution is designed to facilitate the diagnosis of diabetic foot ulcers. Our deep learning model seamlessly categorizes diabetic foot ulcers based on their severity, using CNN and MobileNet integrated with Kotlin for Android. Users receive prompt insights, and users are reminded of the urgency of seeking medical treatment in critical cases by timely notifications. Through the implementation of cutting-edge technology, this combination of proactive healthcare management and image identification represents a significant advancement in the early detection of diabetic foot ulcers and has the potential to enhance patient outcomes.