Predicting Cardiac Arrest in Children with Heart Disease: A Novel Machine Learning Algorithm.
Priscilla YuMichael SkinnerIvie EsangbedoJavier J LasaXilong LiSriraam NatarajanLakshmi RamanPublished in: Journal of clinical medicine (2023)
Our novel machine learning predictive algorithm, which was developed using retrospective data that were collected from the EHR and predicted cardiac arrest in the children that were admitted to a single-center pediatric cardiac intensive care unit, demonstrated a performance that was similar to that of a traditional logistic regression model. While these results are encouraging, future research, including prospective validations with multicenter data, is warranted prior to the implementation of this algorithm as a real-time clinical decision support tool.
Keyphrases
- machine learning
- cardiac arrest
- electronic health record
- clinical decision support
- big data
- intensive care unit
- cardiopulmonary resuscitation
- artificial intelligence
- deep learning
- young adults
- healthcare
- cross sectional
- primary care
- current status
- mechanical ventilation
- left ventricular
- heart failure
- data analysis
- acute respiratory distress syndrome