Remote diagnostics are useful for highly specialized doctors

In the context of modern challenges in the healthcare sector, such as the shortage of highly specialized medical personnel and limited access to quality medical care in remote areas, there is an urgent need for innovative solutions. This article is based on the results of the pilot project "Home Diagnostics" conducted in the Republic of Kazakhstan. The project includes the development and implementation of an integrated software and hardware complex designed to record body sounds, perform otoscopy, pulse oximetry and ensure effective communication between patients and doctors. Special attention is paid to the use of artificial intelligence and machine learning technologies for analyzing medical data and forming diagnoses. The study also addresses important technological aspects, including the use of communication protocols, data processing methods, and considers measures aimed at ensuring the security and confidentiality of medical information. The results of the project demonstrate the significant potential of telemedicine technologies in improving the efficiency of specialized doctors and improving the availability of medical services, especially in low-income and hard-to-reach regions. The article opens up new perspectives in the use of information technologies in medicine and contributes to improving the quality of healthcare. 

1. Dorsey, E. R., & Topol, E. J. (2016). State of Telehealth. New England Journal of Medicine, 375(2), 154-161. https://doi.org/10.1056/NEJMra1601705. (In English).

2. Steinhubl, S. R., Waalen, J., Edwards, A. M., Ariniello, L. M., Mehta, R. R., Ebner, G. S., ... & Topol, E. J. (2015). Digital medicine, on the threshold of a healthcare revolution: A review of current state, challenges, and opportunities for telemedicine. JAMA Internal Medicine, 175(10), 1668-1674. https://doi.org/10.1001/jamainternmed.2015.3568. (In English).

3. Trettel, A., Eissing, L., Augustin, M. (2018). Telemedicine in dermatology: Findings and experiences worldwide – a systematic literature review. Journal of the European Academy of Dermatology and Venereology, 32(2), 215-224. https://doi.org/10.1111/jdv.14698. (In English).

4. Birkeland, S., Vaughan, C., & Eisenberg, L. (2018). The future of otolaryngology telemedicine in the wake of COVID-19: Regulatory and privacy considerations. Otolaryngology – Head and Neck Surgery, 161(1), 1-3. https://doi.org/10.1177/0194599820929449. (In English).

5. Bashshur, R. L., Shannon, G. W., Bashshur, N., & Yellowlees, P. M. (2016). The empirical evidence for telemedicine interventions in mental disorders. Telemedicine and e-Health, 22(2), 87- 113. (In English).

6. Cox A. N., Pilachowski K. A. Allen's astrophysical quantities // Physics Today. – 2000. – Т. 53. – № 10. – С. 77-78. – DOI: https://doi.org/10.1063/1.1325201. (In Russian).

7. Feblovits J. S., Wright A., Singh H., Samal L., Siting D. F. Summation of clinical information: a conceptual model // Journal of Biomedical Informatics. – 2011. – Т. 44. – № 4. – С. 688-699. – DOI: 10.1016/j.jbi.2011.03.008. (In Russian).

8. Kvedar, J., Coye, M. J., & Everett, W. Connected health: a review of technologies and strategies to improve patient care with telemedicine and telehealth. Health Affairs. – 33(2) – 2014. – 194-199 p. (In English).

9. Dirk Beyer, Jan Haltermann, Thomas Lemberger, and Heike Wehrheim. Decomposing software verification into off-the-shelf components: an application to CEGAR. In Proceedings of the 44th International Conference on Software Engineering (ICSE '22). Association for Computing Machinery, New York, NY, USA, - 2022. 536–548p. https://doi.org/10.1145/3510003.3510064. (In English).

10. Whelan, R., Barbey, F.M., Cominetti, M.R. et al. Developments in scalable strategies for detecting early markers of cognitive decline. Transl Psychiatry 12, 473. – 2022. https://doi.org/10.1038/s41398-022-02237-w. (In English).