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dc.contributor.authorNúñez, Agustín
dc.contributor.authorTawfiq, Samer
dc.contributor.authorPolit, Andrés
dc.date.accessioned2024-04-10T01:46:45Z
dc.date.available2024-04-10T01:46:45Z
dc.date.issued2023
dc.identifier10.25237/revchilanestv52n6-04
dc.identifier.issn07164076
dc.identifier.urihttps://hdl.handle.net/20.500.12728/10685
dc.description.abstractArtificial intelligence (AI) is concerned with developing systems that perform tasks that typically require human intelligence. Machine learning (ML) is an important branch of AI and has significant applications in medicine. These applications have allowed advancements in anesthesiology, where algorithms capable of recognizing patterns in arterial waveforms and predicting episodes of hypotension have been developed, reducing postoperative pain and monitoring anesthesia. All of these tools are capable of assisting physicians in event prevention and decision-making. However, it is important to note that, up to now, ML-based tools cannot replace the clinical judgment of an anesthesiologist due to potential biases inherent in initial programming. © 2023 Sociedad de Anestesiologia de Chile. All rights reserved.es_ES
dc.language.isoeses_ES
dc.publisherSociedad de Anestesiologia de Chilees_ES
dc.subjectanesthesiaes_ES
dc.subjectArtificial intelligencees_ES
dc.subjectintraoperative complicationses_ES
dc.subjectintraoperative monitoringes_ES
dc.subjectmachine learninges_ES
dc.titleAnethesia and machine learninges_ES
dc.title.alternativeMachine learning en anestesia. Avances de hoy para la anestesia del mañanaes_ES
dc.typeArticlees_ES


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