Artificial intelligence algorithms predict the efficacy of analgesic cocktails prescribed after orthopedic surgery.

Gerhard Fritsch; Heinz Steltzer; Daniel Oberladstaetter; Carolina Zeller; Hermann Prossinger

doi:10.1371/journal.pone.0280995

Artificial intelligence algorithms predict the efficacy of analgesic cocktails prescribed after orthopedic surgery.

Gerhard Fritsch^* (First author), Heinz Steltzer, Daniel Oberladstaetter, Carolina Zeller, Hermann Prossinger

^*Corresponding author for this work

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

2 Citations (Web of Science)

Original language	English
Pages (from-to)	e0280995
Journal	PLOS ONE
Volume	18
Issue number	2
DOIs	https://doi.org/10.1371/journal.pone.0280995
Publication status	Published - 2023

Keywords

SEVERE POSTOPERATIVE PAIN
MODERATE

Access to Document

10.1371/journal.pone.0280995

Cite this

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title = "Artificial intelligence algorithms predict the efficacy of analgesic cocktails prescribed after orthopedic surgery.",

keywords = "SEVERE POSTOPERATIVE PAIN, MODERATE",

author = "Gerhard Fritsch and Heinz Steltzer and Daniel Oberladstaetter and Carolina Zeller and Hermann Prossinger",

note = "Fritsch:Paracelsus Medical University, Salzburg, Austria",

year = "2023",

doi = "10.1371/journal.pone.0280995",

language = "English",

volume = "18",

pages = "e0280995",

journal = "PLOS ONE",

issn = "1932-6203",

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AU - Fritsch, Gerhard

AU - Steltzer, Heinz

AU - Oberladstaetter, Daniel

AU - Zeller, Carolina

AU - Prossinger, Hermann

N1 - Fritsch:Paracelsus Medical University, Salzburg, Austria

PY - 2023

Y1 - 2023

KW - SEVERE POSTOPERATIVE PAIN

KW - MODERATE

U2 - 10.1371/journal.pone.0280995

DO - 10.1371/journal.pone.0280995

M3 - Original Article

C2 - 36730239

SN - 1932-6203

VL - 18

SP - e0280995

JO - PLOS ONE

JF - PLOS ONE

IS - 2

ER -