An artificial intelligence algorithm for analyzing globus pallidus necrosis after carbon monoxide intoxication

Ming Jen Chan, Ching Chih Hu, Wen Hung Huang, Ching Wei Hsu, Tzung Hai Yen, Cheng Hao Weng*

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review


Globus pallidus necrosis (GPN) is one of typical neurological imaging features in patients with carbon monoxide (CO) poisoning. Current clinical guideline recommends neurological imaging examination for CO-intoxicated patients with conscious disturbance rather than routine screening, which may lead to undiagnosed GPN. We aimed to develop an artificial intelligence algorithm for predicting GPN in CO intoxication patients. We included CO intoxication patients with neurological images between 2000 and 2019 in Chang Gung Memorial Hospital. We collected 41 clinical and laboratory parameters on the first day of admission for algorithm development. We used fivefold cross validation and applied several machine learning algorithms. Random forest classifier (RFC) provided the best predictive performance in our cohort. Among the 261 patients with CO intoxication, 52 patients presented with GPN. The artificial intelligence algorithm using the RFC-based AI model achieved an accuracy = 79.2 ± 2.6%, sensitivity = 77.7%, precision score = 81.9 ± 3.4%, and F1 score = 73.2 ± 1.8%. The area under receiver operating characteristic was approximately 0.64. Top five weighted variables were Platelet count, carboxyhemoglobin, Glasgow Coma scale, creatinine, and hemoglobin. Our RFC-based algorithm is the first to predict GPN in patients with CO intoxication and provides fair predictive ability. Further studies are needed to validate our findings.

Original languageEnglish
Pages (from-to)9603271231190906
JournalHuman and Experimental Toxicology
StatePublished - 01 01 2023

Bibliographical note

Publisher Copyright:
© The Author(s) 2023.


  • Artificial intelligence
  • carbon monoxide
  • globus pallidus necrosis
  • random forest classifier
  • Globus Pallidus/diagnostic imaging
  • Algorithms
  • Carbon Monoxide Poisoning
  • Humans
  • Artificial Intelligence
  • Retrospective Studies
  • Carbon Monoxide/toxicity
  • Necrosis


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