z-logo
open-access-imgOpen Access
Artificial intelligence in sleep medicine: background and implications for clinicians
Author(s) -
Cathy Goldstein,
Richard B. Berry,
David T. Kent,
David A. Kristo,
Azizi Seixas,
Susan Redline,
M. Brandon Westover
Publication year - 2020
Publication title -
journal of clinical sleep medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.529
H-Index - 92
eISSN - 1550-9397
pISSN - 1550-9389
DOI - 10.5664/jcsm.8388
Subject(s) - medicine , sleep medicine , gerontology , population , health care , family medicine , psychiatry , sleep disorder , cognition , environmental health , economics , economic growth
Polysomnography remains the cornerstone of objective testing in sleep medicine and results in massive amounts of electrophysiological data, which is well-suited for analysis with artificial intelligence (AI)-based tools. Combined with other sources of health data, AI is expected to provide new insights to inform the clinical care of sleep disorders and advance our understanding of the integral role sleep plays in human health. Additionally, AI has the potential to streamline day-to-day operations and therefore optimize direct patient care by the sleep disorders team. However, clinicians, scientists, and other stakeholders must develop best practices to integrate this rapidly evolving technology into our daily work while maintaining the highest degree of quality and transparency in health care and research. Ultimately, when harnessed appropriately in conjunction with human expertise, AI will improve the practice of sleep medicine and further sleep science for the health and well-being of our patients.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom