Autors: Borovska, P. I., Ivanova, D. A., Kadurin, V. V.
Title: Experimental Framework for the Investigations in Internet of Medical Imaging Things Ecosystem
Keywords: Internet of Medical Imaging Thinks (IoMIT), Deep Learning, Framework Caffe, Tensor Flow

Abstract: The paper introduces the new technological revolution in digital world, the Internet of Things (IoT) and the opportunities for its application medicine and healthcare. Futhermore, the paper reviews and analyzes the machine learning approaches and methods for big data analytics in IoMIT ecosystem. The main goal of the paper is to present the experimental framework for investigations in Internet of Medical Imaging Thinks (IoMIT). The proposed experimental framework consists of deep learning framework Caffe or Tensor Flow used for training the Machine Learning model and mobile application that utilizes this trained model and the build in camera for medical images analysis. The framework lays the foundation for personal medical assistant apps which will enable patient to pre-diagnose symptoms or verify doctor’s diagnosis. Finally, the preliminary investigations, result analyses and future works are discussed.

References

    Issue

    international conference QED'17 “Children in the Digital Era”, 2018, Bulgaria,

    Copyright QED'17 “Children in the Digital Era”

    Цитирания (Citation/s):
    1. A review on IoT based medical imaging technology for healthcare applications - 2019 - в издания, индексирани в Scopus или Web of Science

    Вид: публикация в международен форум