Document Type
Article
Publication Date
2019
Abstract
The intersection of global broadband technology and miniaturized high-capability computing devices has led to a revolution in the delivery of healthcare and the birth of telemedicine and mobile health (mHealth). Rapid advances in handheld imaging devices with other mHealth devices such as smartphone apps and wearable devices are making great strides in the field of cardiovascular imaging like never before. Although these technologies offer a bright promise in cardiovascular imaging, it is far from straightforward. The massive data influx from telemedicine and mHealth including cardiovascular imaging supersedes the existing capabilities of current healthcare system and statistical software. Artificial intelligence with machine learning is the one and only way to navigate through this complex maze of the data influx through various approaches. Deep learning techniques are further expanding their role by image recognition and automated measurements. Artificial intelligence provides limitless opportunity to rigorously analyze data. As we move forward, the futures of mHealth, telemedicine and artificial intelligence are increasingly becoming intertwined to give rise to precision medicine.
Digital Commons Citation
Seetharam, Karthik; Kagiyama, Nobuyuki; and Sengupta, Partho P., "Application of Mobile Health, Telemedicine and Artificial Intelligence to Echocardiography" (2019). Faculty & Staff Scholarship. 2084.
https://researchrepository.wvu.edu/faculty_publications/2084
Source Citation
Seetharam, K., Kagiyama, N., & Sengupta, P. P. (2019). Application of mobile health, telemedicine and artificial intelligence to echocardiography. Echo Research and Practice, 6(2), R41–R52. https://doi.org/10.1530/erp-18-0081
Comments
© 2019 The authors 2019 This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License