Overview and Clinical Applications of Artificial Intelligence and Machine Learning in Cardiac Anesthesiology.
J Cardiothorac Vasc Anesth
; 38(5): 1211-1220, 2024 May.
Article
en En
| MEDLINE
| ID: mdl-38453558
ABSTRACT
Artificial intelligence- (AI) and machine learning (ML)-based applications are becoming increasingly pervasive in the healthcare setting. This has in turn challenged clinicians, hospital administrators, and health policymakers to understand such technologies and develop frameworks for safe and sustained clinical implementation. Within cardiac anesthesiology, challenges and opportunities for AI/ML to support patient care are presented by the vast amounts of electronic health data, which are collected rapidly, interpreted, and acted upon within the periprocedural area. To address such challenges and opportunities, in this article, the authors review 3 recent applications relevant to cardiac anesthesiology, including depth of anesthesia monitoring, operating room resource optimization, and transthoracic/transesophageal echocardiography, as conceptual examples to explore strengths and limitations of AI/ML within healthcare, and characterize this evolving landscape. Through reviewing such applications, the authors introduce basic AI/ML concepts and methodologies, as well as practical considerations and ethical concerns for initiating and maintaining safe clinical implementation of AI/ML-based algorithms for cardiac anesthesia patient care.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Inteligencia Artificial
/
Anestesiología
Límite:
Humans
Idioma:
En
Revista:
J Cardiothorac Vasc Anesth
Asunto de la revista:
ANESTESIOLOGIA
/
CARDIOLOGIA
Año:
2024
Tipo del documento:
Article