Machine learning-based systems for the anticipation of adverse events after pediatric cardiac surgery
P Garcia-Canadilla, A Isabel-Roquero… - Frontiers in …, 2022 - frontiersin.org
Pediatric congenital heart disease (CHD) patients are at higher risk of postoperative
complications and clinical deterioration either due to their underlying pathology or due to the …
complications and clinical deterioration either due to their underlying pathology or due to the …
[HTML][HTML] Performance drift in machine learning models for cardiac surgery risk prediction: retrospective analysis
Background: The Society of Thoracic Surgeons and European System for Cardiac Operative
Risk Evaluation (EuroSCORE) II risk scores are the most commonly used risk prediction …
Risk Evaluation (EuroSCORE) II risk scores are the most commonly used risk prediction …
Application of machine learning and natural language processing for predicting stroke-associated pneumonia
Background Identifying patients at high risk of stroke-associated pneumonia (SAP) may
permit targeting potential interventions to reduce its incidence. We aimed to explore the …
permit targeting potential interventions to reduce its incidence. We aimed to explore the …
Predicting pediatric emergence delirium using data-driven machine learning applied to electronic health record dataset at a quaternary care pediatric hospital
H Yu, AF Simpao, VM Ruiz, O Nelson, WT Muhly… - JAMIA …, 2023 - academic.oup.com
Objectives Pediatric emergence delirium is an undesirable outcome that is understudied.
Development of a predictive model is an initial step toward reducing its occurrence. This …
Development of a predictive model is an initial step toward reducing its occurrence. This …
Risk for Suicide Attempts Assessed Using the Patient Health Questionnaire–9 Modified for Teens
F Tsui, VM Ruiz, ND Ryan, L Shi, NM Melhem… - JAMA Network …, 2024 - jamanetwork.com
Importance Suicide is a leading cause of death in US youths. Objective To assess whether
screening with supplemental items 10 to 13 on the Patient Health Questionnaire–9 modified …
screening with supplemental items 10 to 13 on the Patient Health Questionnaire–9 modified …
Predicting cardiac arrest in children with heart disease: a novel machine learning algorithm
P Yu, M Skinner, I Esangbedo, JJ Lasa, X Li… - Journal of clinical …, 2023 - mdpi.com
Background: Children with congenital and acquired heart disease are at a higher risk of
cardiac arrest compared to those without heart disease. Although the monitoring of …
cardiac arrest compared to those without heart disease. Although the monitoring of …
Prediction of Return of Spontaneous Circulation in a Pediatric Swine Model of Cardiac Arrest Using Low-Resolution Multimodal Physiological Waveforms
Monitoring physiological waveforms, specifically hemodynamic variables (eg, blood
pressure waveforms) and end-tidal CO 2 (EtCO 2), during pediatric cardiopulmonary …
pressure waveforms) and end-tidal CO 2 (EtCO 2), during pediatric cardiopulmonary …
[HTML][HTML] Continuous Data-Driven Monitoring in Critical Congenital Heart Disease: Clinical Deterioration Model Development
RS Zoodsma, R Bosch, T Alderliesten, CW Bollen… - JMIR cardio, 2023 - cardio.jmir.org
Background: Critical congenital heart disease (cCHD)—requiring cardiac intervention in the
first year of life for survival—occurs globally in 2-3 of every 1000 live births. In the critical …
first year of life for survival—occurs globally in 2-3 of every 1000 live births. In the critical …
Predicting Decompensation Risk in Intensive Care Unit Patients Using Machine Learning
Patients in Intensive Care Units (ICU) face the threat of decompensation, a rapid decline in
health associated with a high risk of death. This study focuses on creating and evaluating …
health associated with a high risk of death. This study focuses on creating and evaluating …
Performance drift is a major barrier to the safe use of machine learning in cardiac surgery
ABSTRACT Objectives The Society of Thoracic Surgeons (STS), and EuroSCORE II (ES II)
risk scores, are the most commonly used risk prediction models for adult cardiac surgery …
risk scores, are the most commonly used risk prediction models for adult cardiac surgery …