ABSTRACT. This article presents an empirical study carried out to evaluate and analyze artificial intelligence-driven smart healthcare services. Building my argument by drawing on data collected from AT&T, Business Insider, Deloitte, IDC, McKinsey & Co., PAC, and Statista, I performed analyses and made estimates regarding number of machine-to-machine connections worldwide (2014–2021, in billions), how the vast majority of Internet of Medical Things is deployed on the operational side of healthcare (%), how digitized organizations source capabilities and talent needed for artificial intelligence work (% of respondents), percentage of connected medical devices today and in five years’ time, U.S. wearable ownership by demographics (%), and most significant barriers organizations face in adopting artificial intelligence (% of respondents). Data collected from 4,400 respondents are tested against the research model by using structural equation modeling.

Keywords: smart healthcare service; wearable medical device; body sensor network

How to cite: Durkin, Kerry (2019). “Artificial Intelligence-driven Smart Healthcare Services, Wearable Medical Devices, and Body Sensor Networks,” American Journal of Medical Research 6(2): 37–42. doi:10.22381/AJMR6220195

Received 16 June 2019 • Received in revised form 17 September 2019
Accepted 18 September 2019 • Available online 22 September 2019