[HTML][HTML] Artificial intelligence in the diagnosis and detection of heart failure: the past, present, and future

F Yasmin, SMI Shah, A Naeem… - Reviews in …, 2021 - imrpress.com
Artificial Intelligence (AI) performs human intelligence-dependant tasks using tools such as
Machine Learning, and its subtype Deep Learning. AI has incorporated itself in the field of …

Rapid response systems

PG Lyons, DP Edelson, MM Churpek - Resuscitation, 2018 - Elsevier
Introduction Rapid response systems are commonly employed by hospitals to identify and
respond to deteriorating patients outside of the intensive care unit. Controversy exists about …

European resuscitation council guidelines for resuscitation 2015: section 3. Adult advanced life support

J Soar, JP Nolan, BW Böttiger, GD Perkins, C Lott… - Resuscitation, 2015 - Elsevier
Adult advanced life support (ALS) includes advanced interventions after basic life support
has started and when appropriate an automated external defibrillator (AED) has been used …

European resuscitation council guidelines for resuscitation 2010 section 4. Adult advanced life support

CD Deakin, JP Nolan, J Soar, K Sunde… - …, 2010 - resuscitationjournal.com
Heart rhythms associated with cardiac arrest are divided into two groups: shockable rhythms
(ventricular fibrillation/pulseless ventricular tachycardia (VF/VT)) and non-shockable rhythms …

An algorithm based on deep learning for predicting in‐hospital cardiac arrest

J Kwon, Y Lee, Y Lee, S Lee, J Park - Journal of the American …, 2018 - Am Heart Assoc
Background In‐hospital cardiac arrest is a major burden to public health, which affects
patient safety. Although traditional track‐and‐trigger systems are used to predict cardiac …

ViEWS—towards a national early warning score for detecting adult inpatient deterioration

DR Prytherch, GB Smith, PE Schmidt, PI Featherstone - Resuscitation, 2010 - Elsevier
AIM OF STUDY: To develop a validated, paper-based, aggregate weighted track and trigger
system (AWTTS) that could serve as a template for a national early warning score (EWS) for …

[HTML][HTML] Machine learning–based early warning systems for clinical deterioration: systematic sco** review

S Muralitharan, W Nelson, S Di, M McGillion… - Journal of medical …, 2021 - jmir.org
Background Timely identification of patients at a high risk of clinical deterioration is key to
prioritizing care, allocating resources effectively, and preventing adverse outcomes. Vital …

“Identifying the hospitalised patient in crisis”—a consensus conference on the afferent limb of rapid response systems

MA DeVita, GB Smith, SK Adam, I Adams-Pizarro… - Resuscitation, 2010 - Elsevier
BACKGROUND: Most reports of Rapid Response Systems (RRS) focus on the efferent,
response component of the system, although evidence suggests that improved vital sign …

Identification of deteriorating patients on general wards; measurement of vital parameters and potential effectiveness of the Modified Early Warning Score

J Ludikhuize, SM Smorenburg, SE de Rooij… - Journal of critical …, 2012 - Elsevier
BACKGROUND AND PURPOSE: Clear and detectable signs of deterioration have been
shown to be present in many patients multiple hours before undergoing a serious life …

The value of vital sign trends for detecting clinical deterioration on the wards

MM Churpek, R Adhikari, DP Edelson - Resuscitation, 2016 - Elsevier
Aim Early detection of clinical deterioration on the wards may improve outcomes, and most
early warning scores only utilize a patient's current vital signs. The added value of vital sign …