TY - JOUR
T1 - Artificial Intelligence and the Practice of Neurology in 2035
T2 - The Neurology Future Forecasting Series
AU - Jones, David T.
AU - Kerber, Kevin A.
N1 - Funding Information:
D.T. Jones has received grant funding from the NIH and Minnesota Partnership for Biotechnology and Medical Genomics. K.A. Kerber has received grant funding from NIH, AHRQ, and Decibel, Inc.; served as a consultant for the American Academy of Neurology and for Bind Inc.; served as section editor (Innovations in Care Delivery) of Neurology®; and received honorarium from Elsevier and publishing royalties from Oxford University Press. Go to Neurology.org/N for full disclosures.
Publisher Copyright:
© American Academy of Neurology.
PY - 2022/2/8
Y1 - 2022/2/8
N2 - High-quality health care delivery relies on a complex orchestration of the flow of patient data. Incorporating advanced artificial intelligence (AI) technologies into this delivery system has tremendous potential to improve health care, but also carries with it unique challenges. The nature of neurologic disease, and the current state of neurologic care delivery, makes this area of medicine well positioned for AI-driven innovation by 2035. Business, ethics, regulation, and medical education will need to evolve in concert. The information technology and data standards requirements for this potential transformation are underappreciated and will be a major driver of changes across the industry. Using AI on patient data to drive health care innovation to improve patients' lives as the primary goal will facilitate widespread acceptance and adoption of the practices required for a successful AI transformation in neurology. In planning the incorporation of AI into clinical practice, the tenets of rigorous research will need to be vigilantly applied to prevent unwarranted costs and inconveniences while promoting meaningful health outcomes.
AB - High-quality health care delivery relies on a complex orchestration of the flow of patient data. Incorporating advanced artificial intelligence (AI) technologies into this delivery system has tremendous potential to improve health care, but also carries with it unique challenges. The nature of neurologic disease, and the current state of neurologic care delivery, makes this area of medicine well positioned for AI-driven innovation by 2035. Business, ethics, regulation, and medical education will need to evolve in concert. The information technology and data standards requirements for this potential transformation are underappreciated and will be a major driver of changes across the industry. Using AI on patient data to drive health care innovation to improve patients' lives as the primary goal will facilitate widespread acceptance and adoption of the practices required for a successful AI transformation in neurology. In planning the incorporation of AI into clinical practice, the tenets of rigorous research will need to be vigilantly applied to prevent unwarranted costs and inconveniences while promoting meaningful health outcomes.
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U2 - 10.1212/WNL.0000000000013200
DO - 10.1212/WNL.0000000000013200
M3 - Article
C2 - 35131918
AN - SCOPUS:85124316539
SN - 0028-3878
VL - 98
SP - 238
EP - 245
JO - Neurology
JF - Neurology
IS - 6
ER -