Role of Artificial Intelligence in TeleStroke: An Overview

Faryal Ali, Umair Hamid, Osama Zaidat, Danish Bhatti, Junaid Siddiq Kalia

Research output: Contribution to journalReview articlepeer-review

11 Scopus citations


Teleneurology has provided access to neurological expertise and state-of-the-art stroke care where previously they have been inaccessible. The use of Artificial Intelligence with machine learning to assist telestroke care can be revolutionary. This includes more rapid and more reliable diagnosis through imaging analysis as well as prediction of hospital course and 3-month prognosis. Intelligent Electronic Medical Records can search free text and provide decision assistance by analyzing patient charts. Speech recognition has advanced enough to be reliable and highly convenient. Smart contextually aware communication and alert programs can enhance efficiency of patient flow and improve outcomes. Automated data collection and analysis can make quality improvement and research projects quicker and much less burdensome. Despite current challenges, these synergistic technologies hold immense promise in enhancing the clinician experience, helping to reduce physician burnout while improving patient health outcomes at a lower cost. This brief overview discusses the multifaceted potential of AI use in telestroke.

Original languageEnglish (US)
Article number559322
JournalFrontiers in Neurology
StatePublished - Oct 7 2020


  • artificial intelligence
  • machine learning
  • telehealth
  • telemedicine
  • teleneurology
  • telestroke

ASJC Scopus subject areas

  • Neurology
  • Clinical Neurology


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