JIMHOpen Access

Journal of Intelligent Medicine and Healthcare

ISSN:(print)
ISSN:(online)
Publication Frequency:Quarterly

  • Online
    Articles

    8

  • on board
    editors

    13

About the Journal

Innovation and rapid technological development in intelligent medicine and healthcare impacts profoundly on many aspects of people’s life. It is believed that developing advanced intelligent algorithms and systems has the potential to save medical resources, reduce administrative costs and burdens, improve integration between medical worker and care providers, reduce medical errors, and improve medical and healthcare quality and patient outcomes. Along with the world’s population growing and aging, challenges in medicine and healthcare on a global scale are very apparent. The vision of Journal of Intelligent Medicine and Healthcare is to attack these apparent challenges through the design of algorithms, mathematical methods, systems, devices, and policies for medicine and healthcare in an intelligent way.

  • Open Access

    ARTICLE

    CNN-LSTM Face Mask Recognition Approach to Curb Airborne Diseases COVID-19 as a Case

    Journal of Intelligent Medicine and Healthcare, Vol.1, No.2, pp. 55-68, 2022, DOI:10.32604/jimh.2022.033058
    Abstract The COVID-19 outbreak has taken a toll on humankind and the world’s health to a breaking point, causing millions of deaths and cases worldwide. Several preventive measures were put in place to counter the escalation of COVID-19. Usage of face masks has proved effective in mitigating various airborne diseases, hence immensely advocated by the WHO (World Health Organization). A compound CNN-LSTM network is developed and employed for the recognition of masked and none masked personnel in this paper. 3833 RGB images, including 1915 masked and 1918 unmasked images sampled from the Real-World Masked Face Dataset (RMFD) and the Simulated Masked… More >

  • Open Access

    ARTICLE

    Homogeneous Management and Application of Appropriate Technology for TCM Care in County Medical Communities

    Journal of Intelligent Medicine and Healthcare, Vol.1, No.2, pp. 69-77, 2022, DOI:10.32604/jimh.2022.036288
    Abstract Objective: Explore the homogeneous management of appropriate technology for Traditional Chinese Medicine (TCM) care based on the county medical community platform. Methods: The hospital has formed a county medical community since 2020, based on which the platform develops homogeneous management of appropriate technologies for TCM nursing, establishes a medical training center, a remote consultation center and a TCM nursing quality control center, strengthens the construction of TCM nursing specialties, integrates TCM with public health and consolidates information support. The “321” model was developed, with January 2021 to December 2021 as the post-implementation period and January 2020 to December 2020 as… More >

  • Open Access

    ARTICLE

    ECG Heartbeat Classification Under Dataset Shift

    Journal of Intelligent Medicine and Healthcare, Vol.1, No.2, pp. 79-89, 2022, DOI:10.32604/jimh.2022.036624
    Abstract Electrocardiogram (ECG) is widely used to detect arrhythmia. Atrial fibrillation, atrioventricular block, premature beats, etc. can all be diagnosed by ECG. When the distribution of training data and test data is inconsistent, the accuracy of the model will be affected. This phenomenon is called dataset shift. In the real-world heartbeat classification system, the heartbeat of the training set and test set often comes from patients of different ages and genders, so there are differences in the distribution of data sets. The main challenge in applying machine learning algorithms to clinical AI systems is dataset shift. Test-time adaptation (TTA) aims to… More >

  • Open Access

    ARTICLE

    Retrospective Analysis of Postprandial Glucose-Response Data Collected in a Free-Living Environment

    Journal of Intelligent Medicine and Healthcare, Vol.1, No.2, pp. 91-102, 2022, DOI:10.32604/jimh.2022.038379
    Abstract Postprandial glucose responses provide vital information on an individual’s risk of major diet-related chronic diseases. This study features digital health technology, namely Continuous Glucose Monitoring (CGM) sensors, along with mobile devices (iPhones running an app) used to collect data from individuals and their environment, specifically nutritional information on what they eat and drink. The paper presents a retrospective analysis of data collected during an investigation into the use of a functional drink taken as a supplement with a standardized meal to reduce postprandial responses to that meal. Given that there are consequential differences between individuals in their postprandial glucose responses,… More >

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