Can Artificial Intelligence Enhance Syncope Management?: A JACC: Advances Multidisciplinary Collaborative Statement : State-of-the-Art Review
(2023) In JACC: Advances 2(3).- Abstract
- Syncope, a form of transient loss of consciousness, remains a complex medical condition for which adverse cardiovascular outcomes, including death, are of major concern but rarely occur. Current risk stratification algorithms have not completely delineated which patients benefit from hospitalization and specific interventions. Patients are often admitted unnecessarily and at high cost. Artificial intelligence (AI) and machine learning may help define the transient loss of consciousness event, diagnose the cause, assess short- and long-term risks, predict recurrence, and determine need for hospitalization and therapeutic intervention; however, several challenges remain, including medicolegal and ethical concerns. This collaborative... (More)
- Syncope, a form of transient loss of consciousness, remains a complex medical condition for which adverse cardiovascular outcomes, including death, are of major concern but rarely occur. Current risk stratification algorithms have not completely delineated which patients benefit from hospitalization and specific interventions. Patients are often admitted unnecessarily and at high cost. Artificial intelligence (AI) and machine learning may help define the transient loss of consciousness event, diagnose the cause, assess short- and long-term risks, predict recurrence, and determine need for hospitalization and therapeutic intervention; however, several challenges remain, including medicolegal and ethical concerns. This collaborative statement, from a multidisciplinary group of clinicians, investigators, and scientists, focuses on the potential role of AI in syncope management with a goal to inspire creation of AI-derived clinical decision support tools that may improve patient outcomes, streamline diagnostics, and reduce health-care costs. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2007990b-5fd0-45b9-b04d-ac1032b5c821
- author
- Statz, Giselle M.
; Evans, Aron Z.
; Johnston, Samuel L.
; Adhaduk, Mehul
; Mudireddy, Avinash R.
; Sonka, Milan
; Lee, Sangil
; Barsotti, E. John
; Ricci, Fabrizio
; Dipaola, Franca
; Johansson, Madeleine
LU
; Sheldon, Robert S.
; Thiruganasambandamoorthy, Venkatesh
; Kenny, Rose-Anne
; Bullis, Tyler C.
; Pasupula, Deepak K.
; Heukelom, Jon Van
; Gebska, Milena A.
and Olshansky, Brian
(Less) - organization
- publishing date
- 2023-05
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- syncope
- in
- JACC: Advances
- volume
- 2
- issue
- 3
- article number
- 100323
- publisher
- American College of Cardiology
- external identifiers
-
- scopus:85160337213
- ISSN
- 2772-963X
- DOI
- 10.1016/j.jacadv.2023.100323
- language
- English
- LU publication?
- yes
- id
- 2007990b-5fd0-45b9-b04d-ac1032b5c821
- date added to LUP
- 2023-05-11 23:59:27
- date last changed
- 2024-02-02 04:04:57
@article{2007990b-5fd0-45b9-b04d-ac1032b5c821,
abstract = {{Syncope, a form of transient loss of consciousness, remains a complex medical condition for which adverse cardiovascular outcomes, including death, are of major concern but rarely occur. Current risk stratification algorithms have not completely delineated which patients benefit from hospitalization and specific interventions. Patients are often admitted unnecessarily and at high cost. Artificial intelligence (AI) and machine learning may help define the transient loss of consciousness event, diagnose the cause, assess short- and long-term risks, predict recurrence, and determine need for hospitalization and therapeutic intervention; however, several challenges remain, including medicolegal and ethical concerns. This collaborative statement, from a multidisciplinary group of clinicians, investigators, and scientists, focuses on the potential role of AI in syncope management with a goal to inspire creation of AI-derived clinical decision support tools that may improve patient outcomes, streamline diagnostics, and reduce health-care costs.}},
author = {{Statz, Giselle M. and Evans, Aron Z. and Johnston, Samuel L. and Adhaduk, Mehul and Mudireddy, Avinash R. and Sonka, Milan and Lee, Sangil and Barsotti, E. John and Ricci, Fabrizio and Dipaola, Franca and Johansson, Madeleine and Sheldon, Robert S. and Thiruganasambandamoorthy, Venkatesh and Kenny, Rose-Anne and Bullis, Tyler C. and Pasupula, Deepak K. and Heukelom, Jon Van and Gebska, Milena A. and Olshansky, Brian}},
issn = {{2772-963X}},
keywords = {{syncope}},
language = {{eng}},
number = {{3}},
publisher = {{American College of Cardiology}},
series = {{JACC: Advances}},
title = {{Can Artificial Intelligence Enhance Syncope Management?: A JACC: Advances Multidisciplinary Collaborative Statement : State-of-the-Art Review}},
url = {{http://dx.doi.org/10.1016/j.jacadv.2023.100323}},
doi = {{10.1016/j.jacadv.2023.100323}},
volume = {{2}},
year = {{2023}},
}