Intelligent Telehealth System To Support Epilepsy Diagnosis

被引:9
|
作者
Molina, Edward [1 ]
Ernesto, Camilo [2 ]
Torres, Sarmiento [2 ]
Salazar-Cabrera, Ricardo [1 ]
Lopez, Diego M. [1 ]
Vargas-Canas, Rubiel [2 ]
机构
[1] Univ Cauca, Telemat Dept, Popayan, Cauca, Colombia
[2] Univ Cauca, Dept Phys, Popayan, Cauca, Colombia
关键词
electroencephalogram; electronic health record; machine learning; diagnostic support system; EEG; EHR; SEIZURE DETECTION; AUTOMATED DIAGNOSIS; EEG; ELECTROENCEPHALOGRAPHY; DECOMPOSITION; TRANSMISSION; TRANSFORM;
D O I
10.2147/JMDH.S247878
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Background: Availability and opportunity of epilepsy diagnostic services is a significant challenge, especially in developing countries with a low number of neurologists. The most commonly used test to diagnose epilepsy is electroencephalogram (EEG). A typical EEG recording lasts for 20 to 30 minutes; however, a specialist requires much more time to read it. Furthermore, no evidence was found in the literature on open-source systems for the cost-effective management of patient information using electronic health records (EHR) that adequately integrate EEG analysis for automatic identification of abnormal signals. Objective: To develop an integrated open-source EHR system for the management of the patients' personal, clinical, and EEG data, and for automatic identification of abnormal EEG signals. Methods: The core of the system is an EHR and telehealth service based on the OpenMRS platform. On top of that, we developed an intelligent component to automatically detect abnormal segments of EEG tests using machine learning algorithms, as well as a service to annotate and visualize abnormal segments in EEG signals. Finally, we evaluated the intelligent component and the integrated system using precision, recall, and accuracy metrics. Results: The system allowed to manage patients' information properly, store and manage the EEG tests recorded with a medical EEG device, and to detect abnormal segments of signals with a precision of 85.10%, a recall of 97.16%, and an accuracy of 99.92%. Conclusion: Digital health is a multidisciplinary field of research in which artificial intelligence is playing a significant role in boosting traditional health services. Notably, the developed system could significantly reduce the time a neurologist spends in the reading of an EEG for the diagnosis of epilepsy, saving approximately 65-75% of the time consumed. It can be used in a telehealth environment. In this way, the availability and provision of diagnostic services for epilepsy management could be improved, especially in developing countries where the number of neurologists is low.
引用
收藏
页码:433 / 445
页数:13
相关论文
共 50 条
  • [1] Design of an Intelligent System to Support the Diagnosis of Patients
    Luis Flores, Jose
    Echeverri Arias, Jaime Alberto
    Aristizabal, Miguel
    Marin, Camilo
    2015 10TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI), 2015,
  • [2] Decision Support System to Diagnosis and Classification of Epilepsy in Children
    Rijo, Rui
    Silva, Catarina
    Pereira, Luis
    Goncalves, Dulce
    Agostinho, Margarida
    JOURNAL OF UNIVERSAL COMPUTER SCIENCE, 2014, 20 (06) : 907 - 923
  • [3] An Intelligent Decision Support System for Lung Cancer Diagnosis
    Alsheikhy A.A.
    Said Y.F.
    Shawly T.
    Computer Systems Science and Engineering, 2023, 46 (01): : 779 - 817
  • [4] A conference support system for telehealth
    Tamai, U
    Nakagawa, K
    Yokomori, M
    Nishiyama, S
    JOURNAL OF TELEMEDICINE AND TELECARE, 2000, 6 : 76 - 78
  • [5] An intelligent system to assist the diagnosis of epilepsy disorder in children: a case of study
    Singh-Mugica, Sunaina
    Tovar-Corona, Blanca
    Silva-Ramirez, Martin A.
    Garay Jimenez, Laura-Ivoone
    2016 IEEE HEALTHCARE INNOVATION POINT-OF-CARE TECHNOLOGIES CONFERENCE (HI-POCT), 2016, : 142 - 145
  • [6] Intelligent decision support system for equipment diagnosis and maintenance management
    Zhang, J
    Tu, YL
    Yeung, EHH
    INNOVATION IN TECHNOLOGY MANAGEMENT - THE KEY TO GLOBAL LEADERSHIP: THE KEY TO GLOBAL LEADERSHIP, 1997, : 733 - 733
  • [7] IDSS: An Intelligent Decision Support System for Breast Cancer Diagnosis
    AlSalman, Hussain
    Almutairi, Najiah
    2019 2ND INTERNATIONAL CONFERENCE ON COMPUTER APPLICATIONS & INFORMATION SECURITY (ICCAIS), 2019,
  • [8] An intelligent decision support system for the accurate diagnosis of cervical cancer
    Newaz, Asif
    Muhtadi, Sabiq
    Haq, Farhan Shahriyar
    KNOWLEDGE-BASED SYSTEMS, 2022, 245
  • [9] Intelligent decision support system for the diagnosis of acute myocardial infarction
    Sun, Bai-Qing
    Feng, Ying-Jun
    Pan, Qi-Shu
    Zhang, Chang-Sheng
    Hou, Gui-Ying
    Guan, Zhen-Zhong
    Xu, Jing
    Yu, Ling-Fan
    Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice, 2006, 26 (10): : 141 - 144
  • [10] Intelligent decision support system for diagnosis and maintenance of automated systems
    Patel, SA
    Kamrani, AK
    COMPUTERS & INDUSTRIAL ENGINEERING, 1996, 30 (02) : 297 - 319