Utilizing machine learning dimensionality reduction for risk stratification of chest pain patients in the emergency department

N Liu, ML Chee, ZX Koh, SL Leow, AFW Ho… - BMC medical research …, 2021 - Springer
Background Chest pain is among the most common presenting complaints in the emergency
department (ED). Swift and accurate risk stratification of chest pain patients in the ED may …

Applications of machine learning to undifferentiated chest pain in the emergency department: A systematic review

J Stewart, J Lu, A Goudie, M Bennamoun, P Sprivulis… - PloS one, 2021 - journals.plos.org
Background Chest pain is amongst the most common reason for presentation to the
emergency department (ED). There are many causes of chest pain, and it is important for the …

Prediction of adverse cardiac events in emergency department patients with chest pain using machine learning for variable selection

N Liu, ZX Koh, J Goh, Z Lin, B Haaland, BP Ting… - BMC medical informatics …, 2014 - Springer
Background The key aim of triage in chest pain patients is to identify those with high risk of
adverse cardiac events as they require intensive monitoring and early intervention. In this …

A machine learning model to predict critical care outcomes in patient with chest pain visiting the emergency department

TT Wu, RF Zheng, ZZ Lin, HR Gong, H Li - BMC emergency medicine, 2021 - Springer
Background Currently, the risk stratification of critically ill patient with chest pain is a
challenge. We aimed to use machine learning approach to predict the critical care outcomes …

Development of an ensemble machine learning prognostic model to predict 60-day risk of major adverse cardiac events in adults with chest pain

CJ Kennedy, DG Mark, J Huang, MJ van der Laan… - MedRxiv, 2021 - medrxiv.org
Background Chest pain is the second leading reason for emergency department (ED) visits
and is commonly identified as a leading driver of low-value health care. Accurate …

Risk stratification for prediction of adverse coronary events in emergency department chest pain patients with a machine learning score compared with the TIMI score

N Liu, MAB Lee, AFW Ho… - International …, 2014 - internationaljournalofcardiology.com
Rapid and accurate risk stratification of chest pain patients in the emergency department
(ED) plays an important role in guiding appropriate disposition and early intervention so as …

An innovative scoring system for predicting major adverse cardiac events in patients with chest pain based on machine learning

CC Wu, WD Hsu, YC Wang, WM Kung, IS Tzeng… - Ieee …, 2020 - ieeexplore.ieee.org
Chest pain is a common complaint in the emergency department, but this may prevent a
diagnosis of major adverse cardiac events, a composite of all-cause mortality associated …

A comparative analysis of risk stratification tools for emergency department patients with chest pain

E Burkett, T Marwick, O Thom, AM Kelly - International Journal of …, 2014 - Springer
Background Appropriate disposition of emergency department (ED) patients with chest pain
is dependent on clinical evaluation of risk. A number of chest pain risk stratification tools …

Prospective validation and comparative analysis of coronary risk stratification strategies among emergency department patients with chest pain

DG Mark, J Huang, MV Kene, DR Sax… - Journal of the …, 2021 - Am Heart Assoc
Background Coronary risk stratification is recommended for emergency department patients
with chest pain. Many protocols are designed as “rule‐out” binary classification strategies …

Real-time AI prediction for major adverse cardiac events in emergency department patients with chest pain

PI Zhang, CC Hsu, Y Kao, CJ Chen, YW Kuo… - Scandinavian Journal of …, 2020 - Springer
Background A big-data-driven and artificial intelligence (AI) with machine learning (ML)
approach has never been integrated with the hospital information system (HIS) for predicting …