Recent Solutions in the Field of Automated Monitoring and Quality Control of Telemedical Services
Recent Solutions in the Field of Automated Monitoring and Quality Control of Telemedical Services |
||
|
||
© 2023 by IJETT Journal | ||
Volume-71 Issue-1 |
||
Year of Publication : 2023 | ||
Author : Georgy Stanislavovich Lebedev, Elena Yuryevna Linskaya, Aslan Adal`bievich Tatarkanov, Abas Khasanovich Lampezhev |
||
DOI : 10.14445/22315381/IJETT-V71I1P207 |
How to Cite?
Georgy Stanislavovich Lebedev, Elena Yuryevna Linskaya, Aslan Adal`bievich Tatarkanov, Abas Khasanovich Lampezhev, "Recent Solutions in the Field of Automated Monitoring and Quality Control of Telemedical Services," International Journal of Engineering Trends and Technology, vol. 71, no. 1, pp. 62-78, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I1P207
Abstract
Currently, telemedical services are becoming increasingly widespread. Therefore, for automated and anticipatory control of diseases, pathologies, and medical errors, it is advisable to develop complexes for automated monitoring and control of telemedical services. This study aims to determine the current development level of software packages for computer-aided monitoring and control of telemedical services and to predict future development trends. This study considers Russian and foreign organizations engaged in creating automated distributed monitoring and online quality control systems for telemedical services. A systematic literature review was conducted to identify market leaders and characteristics of existing and emerging systems. This analysis helped determine: the current technical level of the complexes mentioned above, the main technical solutions used and the technical requirements for advanced complexes, and the trends of further industry development. It was found that in the Russian market, no systems allow full control of the quality of informational telemedical services, making such complexes promising for development and commercialization. Proposals for the architecture and functional capabilities of the software complex for automated monitoring and control of telemedical services were formulated.
Keywords
Automated monitoring, Image artifact, Neural network, Quality control, Telemedical service, Telemedicine, Video stream control.
References
[1] Thamanna Nishath et al., “Implementation of Telemedicine in the Care of Patients with Aortic Dissection,” Seminars in Vascular Surgery, vol. 35, no. 1, pp. 43–50, 2022. Crossref, https://doi.org/10.1053/j.semvascsurg.2022.02.001
[2] L. E. Jackson et al., Telemedicine in Rheumatology Care: A Systematic Review, 2022. [Online]. Available: https://www.crd.york.ac.uk/prospero/display_record.php?id=crd42020202063
[3] V. A. Gorelov et al., “Complex Methodological Approach to Introduction of Modern Telemedicine Technologies into the Healthcare System on Federal, Regional and Municipal Levels,” Proceedings of the 2020 International Conference Quality Management, Transport and Information Security, Information Technologies, pp. 468-473, 2020. Crossref, https://doi.org/10.1109/ITQMIS51053.2020.9322864
[4] Abas Hasanovich Lampezhev et al., “Cluster Data Analysis with a Fuzzy Equivalence Relation to Substantiate a Medical Diagnosis,” Emerging Science Journal, vol. 5, no. 5, pp. 688–699, 2021. Crossref, https://doi.org/10.28991/esj-2021-01305
[5] Eric W. Cucchi, Scott E. Kopec, and Craig M. Lilly, “COVID-19 and the Transformation of ICU Telemedicine,” Clinics in Chest Medicine, vol. 43, no. 3, pp. 529–538, 2022. Crossref, https://doi.org/10.1016%2Fj.ccm.2022.05.007
[6] R. J. Kulchar et al., “Telemedicine, Safe Medication Stewardship, and COVID-19: Digital Transformation During a Global Pandemic,” Journal of Interprofessional Education & Practice, vol. 29, p. 100524, 2022. Crossref, https://doi.org/10.1016/j.xjep.2022.100524
[7] GiulianaGeng-Ramos et al., “Telemedicine for the Pediatric Preoperative Assessment During the COVID-19 Pandemic: Evaluating Patient and Provider Satisfaction,” Perioperative Care and Operating Room Management, vol. 27, p. 100252, 2022. Crossref, https://doi.org/10.1016/j.pcorm.2022.100252
[8] Neha Agarwal, Christina Soh, and Adrian Yeow, “Managing Paradoxical Tensions in the Development of a Telemedicine System,” Information and Organization, vol. 32, no. 1, p. 100393, 2022. Crossref, https://doi.org/10.1016/j.infoandorg.2022.100393
[9] Lorella Cannavacciuolo, Guido Capaldo, and Cristina Ponsiglione, “Digital Innovation and Organizational Changes in the Healthcare Sector: Multiple Case Studies of Telemedicine Project Implementation,” Technovation, p. 102550, 2022. https://doi.org/10.1016/j.technovation.2022.102550
[10] Maria E. Knaus et al., “Both Sides of the Screen: Provider and Patient Perspective on Telemedicine in Pediatric Surgery,” Journal of Pediatric Surgery, vol. 57, no. 8, pp. 1614–1621, 2022. Crossref, https://doi.org/10.1016%2Fj.jpedsurg.2022.03.015
[11] A. Khodadad-Saryazdi, “Exploring the Telemedicine Implementation Challenges Through the Process Innovation Approach: A Case Study Research in the French Healthcare Sector,” Technovation, vol. 107, p. 102273, 2021. Crossref, https://doi.org/10.1016/j.technovation.2021.102273
[12] Anna AAvanesova, and Tatyana A.Shamliyan, “Worldwide Implementation of Telemedicine Programs in Association with Research Performance and Health Policy,” Health Policy and Technology, vol. 8, no. 2, pp. 179–191, 2019. Crossref, https://doi.org/10.1016/j.hlpt.2019.04.001
[13] Susan K. Chrostowski, and Mari Tietze, “Using a Telemedicine Cart for an Objective Structured Clinical Examination (OSCE) in Nurse Practitioner Education,” Clinical Simulation in Nursing, vol. 70, pp. 21–27, 2022. Crossref, https://doi.org/10.1016/j.ecns.2022.06.002
[14] J. Macwilliam, I. Hennessey, and G. Cleary, “Telemedicine: Improving Clinical Care and Medical Education in Paediatrics,” Paediatrics and Child Health, vol. 31, no. 10, pp. 388–396, 2021. Crossref, https://doi.org/10.1016/j.paed.2021.07.004
[15] M. M. Shoemaker et al., “Novel Application of Telemedicine and an Alternate EHR Environment for Virtual Clinical Education: A New Model for Primary Care Education During the SARS-Cov-2 Pandemic,” International Journal of Medical Informatics, vol. 153, p. 104526, 2021.
[16] S. C. Haynes, and J. P. Marcin, “Pediatric Telemedicine: Lessons Learned During the Coronavirus Disease 2019 Pandemic and Opportunities for Growth,” Advances in Pediatrics, vol. 69, no. 1, pp. 1–11, 2022. Crossref, https://doi.org/10.1016/j.yapd.2022.04.002
[17] Jay M. Portnoy et al., “Telemedicine and Emerging Technologies for Health Care in Allergy/Immunology,” Journal of Allergy and Clinical Immunology, vol. 145, no. 2, pp. 445–454, 2020. Crossref, https://doi.org/10.1016/j.jaci.2019.12.903
[18] A. Kondakova, and Sergry Kulik, “Intelligent Information System for Telemedicine,” Procedia Computer Science, vol. 169, pp. 240–243, 2020. Crossref, https://doi.org/10.1016/j.procs.2020.02.142
[19] Sushmitha. J et al., "Patient Medical Checkup Using Webapp and IOT," SSRG International Journal of Computer Science and Engineering, vol. 5, no. 8, pp. 15-18, 2018. Crossref, https://doi.org/10.14445/23488387/IJCSE-V5I8P104
[20] M. Salomon et al., “Steganalysis via a Convolutional Neural Network Using Large Convolution Filters for Embedding Process with Same Stego Key: A Deep Learning Approach for Telemedicine,” European Research in Telemedicine, vol. 6, no. 2, pp. 79–92, 2017. Crossref, https://doi.org/10.1016/j.eurtel.2017.06.001
[21] Jennifer Vanessa Mejía Lara, and Ricardo Manuel Arias Velásquez, “Low-Cost Image Analysis with Convolutional Neural Network for Herpes Zoster,” Biomedical Signal Processing and Control, vol. 71(Part B), p. 103250, 2022. Crossref, https://doi.org/10.1016/j.bspc.2021.103250
[22] David Baur, “Convolutional Neural Networks in Spinal Magnetic Resonance Imaging: A Systematic Review,” World Neurosurgery, vol. 166, pp. 60–70, 2022. Crossref, https://doi.org/10.1016/j.wneu.2022.07.0410
[23] M. Mahmood, W. J. Al-Kubaisy, and B. Al-Khateeb, “Using Artificial Neural Network for Multimedia Information Retrieval,” Journal of Southwest Jiaotong University, vol. 54, no. 3, 2019. Crossref, https://doi.org/10.35741/issn.0258-2724.54.3.19
[24] T. I. Götz et al., “Number of Necessary Training Examples for Neural Networks with Different Number of Trainable Parameters,” Journal of Pathology Informatics, vol. 13, p. 100114, 2022. Crossref, https://doi.org/10.1016/j.jpi.2022.100114
[25] Aslan A. Tatarkanov et al., “Using a One-Dimensional Convolution Neural Network to Detect Atrial Fibrillation,” Proceedings of the International Conference on Quality Management, Transport and Information Security, Information Technologies, pp. 560-564, 2021. Crossref, https://doi.org/10.1109/ITQMIS53292.2021.9642733
[26] Aslan Tatarkanov, Islam A. Alexandrovm, and Rasul M. Glashev, “Synthesis of Neural Network Structure for the Analysis of Complex Structured Ocular Fundus Images,” Journal of Applied Engineering Science, vol. 19, no. 2, pp. 344–355, 2021. Crossref, https://doi.org/10.5937/jaes0-31238
[27] Chaochao Ma et al., “Real-World Big-Data Studies in Laboratory Medicine: Current Status, Application, and Future Considerations,” Clinical Biochemistry, vol. 84, pp. 21–30, 2020. Crossref, https://doi.org/10.1016/j.clinbiochem.2020.06.014
[28] Davide Cirillo, and A. Valencia, “Big Data Analytics for Personalized Medicine,” Current Opinion in Biotechnology, vol. 58, pp. 161–167, 2019. Crossref, https://doi.org/10.1016/j.copbio.2019.03.004
[29] ChloéDimeglio “Expectations and Boundaries for Big Data Approaches in Social Medicine,” Journal of Forensic and Legal Medicine, vol. 57, pp. 51–54, 2018. Crossref, https://doi.org/10.1016/j.jflm.2016.11.003
[30] A. H. Lampezhev, I. A. Alexandrov, and V. Gorelov, “Automated Analysis of Big Data From Social Networks as a Way to Compile A Psychological Portrait of a Personality,” Proceedings of the International Conference on Quality Management, Transport and Information Security, Information Technologies, pp. 511-515, 2021. Crossref, https://doi.org/10.1109/ITQMIS53292.2021.9642901
[31] T. Godhavari et al., "An Intelligent System for Monitoring Various Parameters in Irrigation System Using Iot," SSRG International Journal of Electrical and Electronics Engineering, vol. 9, no. 12, pp. 120-125, 2022. Crossref, https://doi.org/10.14445/23488379/IJEEE-V9I12P110
[32] C. J. Puranik, S. Rao, and S. Chennamaneni, “The Perils and Pitfalls of Big Data Analysis in Medicine,” The Ocular Surface, vol. 17, no. 4, pp. 838–839, 2019. Crossref, https://doi.org/10.1016/j.jtos.2019.07.010
[33] Panagiota Galetsi, Korina Katsaliaki, and Sameer Kumar, “The Medical and Societal Impact of Big Data Analytics and Artificial Intelligence Applications in Combating Pandemics: A Review Focused on Covid-19,” Social Science & Medicine, vol. 301, 114973, 2022. Crossref, https://doi.org/10.1016/j.socscimed.2022.114973
[34] Lane F. Donnelly, Robert Grzeszczuk, and Carolina V. Guimaraes,, “Use of Natural Language Processing (NLP) in Evaluation of Radiology Reports: An Update on Applications and Technology Advances,” Seminars in Ultrasound, CT and MRI, vol. 43, no. 2, pp. 176–181, 2022. Crossref, https://doi.org/10.1053/j.sult.2022.02.007
[35] Dhiraj J Pangal et al., “A Guide to Annotation of Neurosurgical Intraoperative Video for Machine Learning Analysis and Computer Vision,” World Neurosurgery, vol. 150, pp. 26–30, 2021. Crossref, https://doi.org/10.1016/j.wneu.2021.03.022
[36] Li, Renjie et al., “Moving Towards Intelligent Telemedicine: Computer Vision Measurement of Human Movement,” Computers in Biology and Medicine, vol. 147, p. 105776, 2022.
[37] Eva Hagberg et al., “Semi-Supervised Learning with Natural Language Processing for Right Ventricle Classification in Echocardiography—A Scalable Approach,” Computers in Biology and Medicine, vol. 143, p. 105282, 2022. Crossref, https://doi.org/10.1016/j.compbiomed.2022.105282
[38] M. Coleman, A. Kumar, and L. Boswell, Can Hybrid Transmission Strategies Ensure Jitter-Free Content to Multi-Screens?, AsiaPacific Broadcasting, 2020. [Online]. Available: https://apb-news.com/can-hybrid-transmission-strategies-ensure-jitter-freecontent-to-multi-screens/
[39] S. Puopolo, “Telestream & Tektronix Video: A Company Integration Powered By Growth and Innovation,” IABM Journal, vol. 109, 2019. TAG Video Systems Launches Realtime Media Platform for Viewer Analytics, Content & Technology, 2021. [Online]. Available: https://content-technology.com/content-delivery/tag-video-systems-launches-realtime-media-platform-for-vieweranalytics/
[40] P. Sandberg, TAG video systems launches realtime media platform for viewer analytics, Content & Technology, 2021. [Online]. Available:https://content-technology.com/content-delivery/tag-video-systems-launches-realtime-media-platform-for-vieweranalytics/
[41] N. Soseman, Bridge Technologies Launchs Integrated Services Monitoring, 2020. [Online]. Available: https://www.thebroadcastbridge.com/content/entry/14936/bridge-technologies-launches-integrated-services-monitoring
[42] Jan Ozer, Elecard Video Quality Estimator: Review, Streaming Media, 2018. [Online]. Available: https://www.streamingmedia.com/articles/readarticle.aspx?articleid=129136
[43] J. B. Lujan et al., “Telemedicine Prototype to Improve Medical Care and Patient and Physician Safety in Lima-Peru,” International Journal of Engineering Trends and Technology, vol. 70, no. 8, pp. 83–96, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I8P208
[44] Joel Ricardo Ligarda Motta et al., “Implementation of a Mobile Application: Sales Optimization in A Peruvian Company,” International Journal of Engineering Trends and Technology, vol. 70, no. 11, pp. 58–69, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I11P206
[45] R. M. Ualiyeva et al., “Peculiarities of the Structure of Male Reproductive System in Trematode Parastrigea Robusta (Trematoda: Strigeidae),” Online Journal of Biological Sciences, vol. 17, no. 2, pp. 88–94, 2017. Crossref, https://doi.org/10.3844/ojbsci.2017.88.94
[46] Rimma Meyramovna Ualiyeva, Sayan Berikovich Zhangazin, and Indira Bulatovna Altayeva, “Structural Organization of Vitelline Cells of Trematode with Undifferentiated Body of Azygia Lucii (Muller, 1776),” Online Journal of Biological Sciences, vol. 22, no. 1, pp. 10–17, 2022. Crossref, https://doi.org/10.3844/ojbsci.2022.10.17
[47] Sharib Ali et al., “A Deep Learning Framework for Quality Assessment and Restoration in Video Endoscopy,” Medical Image Analysis, vol. 68, p. 101900, 2021. Crossref, https://doi.org/10.1016/j.media.2020.101900
[48] Aslan A. Tatarkanov et al., “A Fuzzy Approach to the Synthesis of Cognitive Maps for Modeling Decision Making in Complex Systems,” Emerging Science Journal, vol. 6, no. 2, pp. 368–381, 2022. Crossref, https://doi.org/10.28991/ESJ-2022-06-02-012