AI Medical Compendium Topic:
Intensive Care Units

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Development and external validation of a dynamic risk score for early prediction of cardiogenic shock in cardiac intensive care units using machine learning.

European heart journal. Acute cardiovascular care
AIMS: Myocardial infarction and heart failure are major cardiovascular diseases that affect millions of people in the USA with morbidity and mortality being highest among patients who develop cardiogenic shock. Early recognition of cardiogenic shock ...

[Personalized glycemic management for patients with diabetic ketoacidosis based on machine learning].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To explore the optimal blood glucose-lowering strategies for patients with diabetic ketoacidosis (DKA) to enhance personalized treatment effects using machine learning techniques based on the United States Critical Care Medical Information...

Effectiveness of an Artificial Intelligence-Enabled Intervention for Detecting Clinical Deterioration.

JAMA internal medicine
IMPORTANCE: Inpatient clinical deterioration is associated with substantial morbidity and mortality but may be easily missed by clinicians. Early warning scores have been developed to alert clinicians to patients at high risk of clinical deterioratio...

[Analysis of clinical treatment of acute respiratory distress syndrome assisted by artificial intelligence].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To evaluate the clinical practice of intensive care unit (ICU) physicians at Hebei General Hospital in identifying patients meeting the diagnostic criteria for acute respiratory distress syndrome (ARDS) and the current status of invasive m...

[Constructing a predictive model for the death risk of patients with septic shock based on supervised machine learning algorithms].

Zhonghua wei zhong bing ji jiu yi xue
OBJECTIVE: To construct and validate the best predictive model for 28-day death risk in patients with septic shock based on different supervised machine learning algorithms.

Explainable artificial intelligence model for mortality risk prediction in the intensive care unit: a derivation and validation study.

Postgraduate medical journal
BACKGROUND: The lack of transparency is a prevalent issue among the current machine-learning (ML) algorithms utilized for predicting mortality risk. Herein, we aimed to improve transparency by utilizing the latest ML explicable technology, SHapley Ad...

Pharmaceutical Decision Support System Using Machine Learning to Analyze and Limit Drug-Related Problems in Hospitals.

Studies in health technology and informatics
The health product circuit corresponds to the chain of steps that a medicine goes through in hospital, from prescription to administration. The safety and regulation of all the stages of this circuit are major issues to ensure the safety and protect ...

Treatment Prediction in the ICU Using a Partitioned, Sequential, Deep Time Series Analysis.

Studies in health technology and informatics
We have developed a time-oriented machine-learning tool to predict the binary decision of administering a medication and the quantitative decision regarding the specific dose. We evaluated our tool on the MIMIC-IV ICU database, for three common medic...

[Intelligent rehabilitation platform in intensive care unit].

Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
As the development of rehabilitation medicine and critical care medicine, intensive care rehabilitation has become the focus of attention. With the development of artificial intelligence, wearable devices and non-contact multimodal behavior perceptio...