References
- Al-Ahmad, A. S., and H. Kahtan. 2018. cloud computing review: Features and issues. 2018 International Conference on Smart Computing and Electronic Enterprise (ICSCEE), 1–1779. doi:10.1109/ICSCEE.2018.8538387.
- Alhussein, M., and G. Muhammad. 2018. Voice pathology detection using deep learning on mobile healthcare framework. IEEE Access 6:41034–41. doi:10.1109/ACCESS.2018.2856238.
- Almutairi, K., H. Abdlerazek, and S. Elbakry. 2020. Development of smart healthcare system for visually impaired using speech recognition. International Journal of Advanced Computer Science and Applications 11 (12):647–54. doi:10.14569/IJACSA.2020.0111275.
- Baird, A., and S. Nowak. 2014. Why primary care practices should become digital health information hubs for their patients. BMC Family Practice 15 (1):1–5. doi:10.1186/s12875-014-0190-9.
- Bhosale, Y. H., and K. S. Patnaik. 2022. Application of deep learning techniques in diagnosis of Covid-19 (coronavirus): A systematic review. Neural Process Lett:1–53. doi:10.1007/s11063-022-11023-0.
- Bhosale, Y. H., S. Zanwar, and Z. Ahmed. 2022. Deep convolutional neural network based Covid-19 classification from radiology X-Ray images for IoT enabled devices. International Conference on Advanced Computing and Communication Systems 5: 1398–402.
- Decade of Healthy Ageing: Baseline Report. 2020. https://www.who.int/publications/i/item/9789240017900.
- Demertzis, K., D. Taketzis, D. Tsiotas, L. Magafas, L. Iliadis, and P. Kikiras. 2021. Pandemic analytics by advanced machine learning for improved decision making of COVID-19 crisis. Processes 9(8):1267. Multidisciplinary Digital Publishing Institute. doi:10.3390/pr9081267.
- Demertzis, K., D. Tsiotas, and L. Magafas. 2020. Modeling and Forecasting the COVID-19 temporal spread in Greece: An exploratory approach based on complex network defined splines. International Journal of Environmental Research and Public Health 17(13):4693. Multidisciplinary Digital Publishing Institute. doi:10.3390/ijerph17134693.
- Hochreiter, S. 1991. Untersuchungen zu dynamischen neuronalen Netzen. Master’s thesis, Institut fur Informatik.
- LeCun, Y., B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel. 1989. Backpropagation applied to handwritten zip code recognition. Neural Computation 1 (4):541–51. doi:10.1162/neco.1989.1.4.541.
- Mihalcea, R., and P. Tarau. 2004. TextRank: Bringing order into text. EMNLP 4:404–11.
- Ozdemir, Z., J. Barron, and S. Bandyopadhyay. 2010. An analysis of the adoption of digital health records under switching costs. Information Systems Research 22 (3):491–503. doi:10.1287/isre.1110.0349.
- Punith, A., G. Manish, and M. S. Sumanth. 2021. Design and Implementation of a smart reader for blind and visually impaired people. AIP Conference Proceedings 2317:421–428.
- Qin, B. 2021. Research on the application of intelligent speech recognition technology in medical big data fog computing system. Journal of Decision Systems 1–13. doi:10.1080/12460125.2021.1980943.
- Sekhar, S. R. M., G. Kashyap, A. Bhansali, and K. Singh. 2021. Dysarthric-speech detection using transfer learning with convolutional neural networks. ICT Express 8 (1):61–64. doi:10.1016/j.icte.2021.07.004.
- Shore, J. H., E. Brooks, D. M. Savin, S. M. Manson, and A. M. Libby. 2007. An economic evaluation of telehealth data collection with rural populations. Psychiatric Services 58 (6):830–35. doi:10.1176/ps.2007.58.6.830.