Reliably automating ASA classification: a case for artificial intelligence in preoperative assessment

Y. Vogelaar; Sander F. van den Heuvel; Jaap J. van Rijn; Robert jan Stolker; Kim Batselier; Jan-Wiebe Korstanje

Reliably automating ASA classification: a case for artificial intelligence in preoperative assessment

Y. Vogelaar, Sander F. van den Heuvel, Jaap J. van Rijn, Robert jan Stolker, Kim Batselier, Jan-Wiebe Korstanje

Anesthesiology

Research output: Contribution to conference › Abstract › Academic

Abstract

With 99% of American Society of Anesthesiologists Physical Status III and IV patients correctly being detected by the LS SVM algorithm, the automation of screening for high-risk patients appears feasible, albeit with a false positive rate of 67%. Accuracy could likely be improved by fine-tuning the questionnaire and adding other clinical features (e.g. blood pressure or ECG).

Original language	English
Pages	261
Publication status	Published - 4 Jun 2022
Event	ESAIC - Milan, Italy Duration: 4 Jun 2022 → 6 Jun 2022

Conference

Conference	ESAIC
Country/Territory	Italy
City	Milan
Period	4/06/22 → 6/06/22

Bibliographical note

In: European Journal of Anaesthesiology, Volume 39 I-e Supplement 60 I June 2022

Copyright © 2022 by European Society of Anaesthesiology and Intensive Care.

Access to Document

https://journals.lww.com/ejanaesthesiology/Documents/ESAIC_Abstracts_2022.pdf

Cite this

@conference{aeaf98f41b804b03bf87b880e42bc5a5,

title = "Reliably automating ASA classification: a case for artificial intelligence in preoperative assessment",

abstract = "With 99% of American Society of Anesthesiologists Physical Status III and IV patients correctly being detected by the LS SVM algorithm, the automation of screening for high-risk patients appears feasible, albeit with a false positive rate of 67%. Accuracy could likely be improved by fine-tuning the questionnaire and adding other clinical features (e.g. blood pressure or ECG).",

author = "Y. Vogelaar and {van den Heuvel}, {Sander F.} and {van Rijn}, {Jaap J.} and Stolker, {Robert jan} and Kim Batselier and Jan-Wiebe Korstanje",

note = "In: European Journal of Anaesthesiology, Volume 39 I-e Supplement 60 I June 2022 Copyright {\textcopyright} 2022 by European Society of Anaesthesiology and Intensive Care.; ESAIC ; Conference date: 04-06-2022 Through 06-06-2022",

year = "2022",

month = jun,

day = "4",

language = "English",

pages = "261",

}

TY - CONF

T1 - Reliably automating ASA classification

T2 - ESAIC

AU - Vogelaar, Y.

AU - van den Heuvel, Sander F.

AU - van Rijn, Jaap J.

AU - Stolker, Robert jan

AU - Batselier, Kim

AU - Korstanje, Jan-Wiebe

PY - 2022/6/4

Y1 - 2022/6/4

N2 - With 99% of American Society of Anesthesiologists Physical Status III and IV patients correctly being detected by the LS SVM algorithm, the automation of screening for high-risk patients appears feasible, albeit with a false positive rate of 67%. Accuracy could likely be improved by fine-tuning the questionnaire and adding other clinical features (e.g. blood pressure or ECG).

AB - With 99% of American Society of Anesthesiologists Physical Status III and IV patients correctly being detected by the LS SVM algorithm, the automation of screening for high-risk patients appears feasible, albeit with a false positive rate of 67%. Accuracy could likely be improved by fine-tuning the questionnaire and adding other clinical features (e.g. blood pressure or ECG).

M3 - Abstract

SP - 261

Y2 - 4 June 2022 through 6 June 2022

ER -

Reliably automating ASA classification: a case for artificial intelligence in preoperative assessment

Abstract

Conference

Bibliographical note

Access to Document

Fingerprint

Cite this