AIMC Topic: Intensive Care Units
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Early prediction of hemodynamic interventions in the intensive care unit using machine learning.
Critical care (London, England)
Nov 14, 2021
BACKGROUND: Timely recognition of hemodynamic instability in critically ill patients enables increased vigilance and early treatment opportunities. We develop the Hemodynamic Stability Index (HSI), which highlights situational awareness of possible h...
A novel artificial intelligence based intensive care unit monitoring system: using physiological waveforms to identify sepsis.
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Oct 25, 2021
A massive amount of multimodal data are continuously collected in the intensive care unit (ICU) along each patient stay, offering a great opportunity for the development of smart monitoring devices based on artificial intelligence (AI). The two main ...
The Potential Cost-Effectiveness of a Machine Learning Tool That Can Prevent Untimely Intensive Care Unit Discharge.
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
Oct 22, 2021
OBJECTIVES: The machine learning prediction model Pacmed Critical (PC), currently under development, may guide intensivists in their decision-making process on the most appropriate time to discharge a patient from the intensive care unit (ICU). Given...
A Machine Learning Model for Accurate Prediction of Sepsis in ICU Patients.
Frontiers in public health
Oct 15, 2021
Although numerous studies are conducted every year on how to reduce the fatality rate associated with sepsis, it is still a major challenge faced by patients, clinicians, and medical systems worldwide. Early identification and prediction of patients...
Sentiment Analysis Based on the Nursing Notes on In-Hospital 28-Day Mortality of Sepsis Patients Utilizing the MIMIC-III Database.
Computational and mathematical methods in medicine
Oct 13, 2021
In medical visualization, nursing notes contain rich information about a patient's pathological condition. However, they are not widely used in the prediction of clinical outcomes. With advances in the processing of natural language, information begi...
Artificial intelligence forecasting mortality at an intensive care unit and comparison to a logistic regression system.
Einstein (Sao Paulo, Brazil)
Oct 11, 2021
OBJECTIVE: To explore an artificial intelligence approach based on gradient-boosted decision trees for prediction of all-cause mortality at an intensive care unit, comparing its performance to a recent logistic regression system in the literature, an...
Feasibility of machine integrated point of care lung ultrasound automatic B-lines tool in the Corona-virus 2019 critical care unit.
Critical care (London, England)
Sep 24, 2021
Risk prediction of clinical adverse outcomes with machine learning in a cohort of critically ill patients with atrial fibrillation.
Scientific reports
Sep 23, 2021
Critically ill patients affected by atrial fibrillation are at high risk of adverse events: however, the actual risk stratification models for haemorrhagic and thrombotic events are not validated in a critical care setting. With this paper we aimed t...
Accurate diagnosis of sepsis using a neural network: Pilot study using routine clinical variables.
Computer methods and programs in biomedicine
Aug 31, 2021
BACKGROUND AND OBJECTIVES: Sepsis is a severe infection that increases mortality risk and is one if the main causes of death in intensive care units. Accurate detection is key to successful interventions, but diagnosis of sepsis is complicated becaus...
Machine learning identifies ICU outcome predictors in a multicenter COVID-19 cohort.
Critical care (London, England)
Aug 17, 2021
BACKGROUND: Intensive Care Resources are heavily utilized during the COVID-19 pandemic. However, risk stratification and prediction of SARS-CoV-2 patient clinical outcomes upon ICU admission remain inadequate. This study aimed to develop a machine le...
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