A Clinical Decision Support System based on an Unobtrusive Mobile App

@inproceedings{Richardson2019ACD,
  title={A Clinical Decision Support System based on an Unobtrusive Mobile App},
  author={A. Richardson and Avigail Perl and Sapir Natan and Gil Segev},
  booktitle={ICT4AWE},
  year={2019}
}
  • A. Richardson, Avigail Perl, +1 author Gil Segev
  • Published in ICT4AWE 2019
  • Computer Science
    • Clinical decision support systems typically rely on medical records and information collected in the doctor’s office. We propose a clinical decision support system that uses data collected from patients continuously and in an unobtrusive manner. The system uses data collected from a mobile app installed on the patient’s device (such as a mobile phone, smart-watch etc). The app collects data without user interference and combines it with conventional medical records. Our system uses machine… CONTINUE READING
    View via Publisher
    doi.org

    Figures and Topics from this paper

    Figures

    Explore Further: Topics Discussed in This Paper

    References

    SHOWING 1-10 OF 23 REFERENCES
    Assessment of a personalized and distributed patient guidance system
    • 41
    • PDF
    Making Healthcare More Accessible , Better , Faster , and Cheaper : The MobiGuide Project
    • 24
    • PDF
    Supporting tele-health and AI-based clinical decision making with sensor data fusion and semantic interpretation: The USEFIL case study
    • 27
    Feasibility of Using a Mobile Application for the Monitoring and Management of Stroke-Associated Risk Factors
    • 22
    • PDF
    A distributed clinical decision support system architecture
    • 46
    • Highly Influential
    Information and decision support needs in patients with type 2 diabetes
    • 18
    A Smartphone Client-Server Teleradiology System for Primary Diagnosis of Acute Stroke
    • 87
    Mobile Applications for Stroke: A Survey and a Speech Classification Approach
    • 2
    • PDF
    Development of Smartphone Application That Aids Stroke Screening and Identifying Nearby Acute Stroke Care Hospitals
    • 30
    Clinical decision support systems for improving diagnostic accuracy and achieving precision medicine
    • 163
    • PDF