Signal processing and machine learning algorithm to classify anaesthesia depth

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

Translated title of the contribution	Signal processing and machine learning algorithm to classify anaesthesia depth
Original language	Undefined/Unknown
Pages (from-to)	1-8
Number of pages	7
Journal	BMJ health ; care informatics
DOIs	https://doi.org/10.1136/bmjhci-2023-100823
State	Published - 3 Oct 2023

Article Classification

@article{cf57e5efe9ee45f29d2d3d6bddbe6822,

title = "Signal processing and machine learning algorithm to classify anaesthesia depth",

author = "\{Mosquera Dussan\}, \{Oscar Leonardo\} and \{Botero Rosas\}, \{Daniel Alfonso\} and \{Tuta Quintero\}, \{Eduardo Andres\}",

year = "2023",

month = oct,

day = "3",

doi = "10.1136/bmjhci-2023-100823",

language = "Indefinido/desconocido",

pages = "1--8",

journal = "BMJ health ; care informatics",

issn = "2632-1009",

publisher = "BMJ Publishing Group",

}

TY - JOUR

T1 - Signal processing and machine learning algorithm to classify anaesthesia depth

AU - Botero Rosas, Daniel Alfonso

A2 - Mosquera Dussan, Oscar Leonardo

A2 - Tuta Quintero, Eduardo Andres

PY - 2023/10/3

Y1 - 2023/10/3

U2 - 10.1136/bmjhci-2023-100823

DO - 10.1136/bmjhci-2023-100823

M3 - Artículo

SN - 2632-1009

SP - 1

EP - 8

JO - BMJ health ; care informatics

JF - BMJ health ; care informatics

ER -