AIMC Topic: Intensive Care Units

Clear Filters Showing 651 to 660 of 694 articles

Predicting Length of Stay for Cardiovascular Hospitalizations in the Intensive Care Unit: Machine Learning Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Predicting Cardiovascular Length of stay based hospitalization at the time of patients' admitting to the coronary care unit (CCU) or (cardiac intensive care units CICU) is deemed as a challenging task to hospital management systems globally. Recently...
Electronic Health Records Length of Stay Coronary Care Units Humans Machine Learning Intensive Care Units
View on PubMed DOI

A machine learning method for automatic detection and classification of patient-ventilator asynchrony.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Patients suffering from respiratory failure are often put on assisted mechanical ventilation. Patient-ventilator asynchrony (PVA) can occur during mechanical ventilation, which cause damage to the lungs and has been linked to increased mortality in t...
Humans Ventilators, Mechanical Machine Learning Respiration Intensive Care Units Respiration, Artificial
View on PubMed DOI

Predictive Modeling of Pressure Injury Risk in Patients Admitted to an Intensive Care Unit.

American journal of critical care : an official publication, American Association of Critical-Care Nurses Jul 1, 2020
BACKGROUND: Pressure injuries are an important problem in hospital care. Detecting the population at risk for pressure injuries is the first step in any preventive strategy. Available tools such as the Norton and Braden scales do not take into accoun...
Male Middle Aged Risk Assessment Adolescent Young Adult Adult Machine Learning Sensitivity and Specificity Aged Humans Data Mining Intensive Care Units Aged, 80 and over Female Child Electronic Health Records APACHE Critical Care Risk Factors Pressure Ulcer Hospitals, University Hemoglobins
View on PubMed DOI

Computer vision's potential to improve health care.

Lancet (London, England) May 16, 2020
Artificial Intelligence Algorithms Computers Electronic Health Records Clinical Decision-Making Delivery of Health Care Intensive Care Units Humans Video Recording Patient Harm Vision, Ocular Surgeons United States Medicare
View on PubMed DOI

Prediction of an Acute Hypotensive Episode During an ICU Hospitalization With a Super Learner Machine-Learning Algorithm.

Anesthesia and analgesia May 1, 2020
BACKGROUND: Acute hypotensive episodes (AHE), defined as a drop in the mean arterial pressure (MAP) <65 mm Hg lasting at least 5 consecutive minutes, are among the most critical events in the intensive care unit (ICU). They are known to be associated...
Cohort Studies Predictive Value of Tests Acute Disease Hypotension Aged Male Middle Aged Humans Machine Learning Female Hospitalization Algorithms Intensive Care Units
View on PubMed DOI

On classifying sepsis heterogeneity in the ICU: insight using machine learning.

Journal of the American Medical Informatics Association : JAMIA Mar 1, 2020
OBJECTIVES: Current machine learning models aiming to predict sepsis from electronic health records (EHR) do not account 20 for the heterogeneity of the condition despite its emerging importance in prognosis and treatment. This work demonstrates the ...
Diagnosis, Differential Organ Dysfunction Scores Electronic Health Records Sensitivity and Specificity Sepsis Humans Machine Learning Intensive Care Units
View on PubMed DOI

Temporal convolutional networks allow early prediction of events in critical care.

Journal of the American Medical Informatics Association : JAMIA Mar 1, 2020
OBJECTIVE: Clinical interventions and death in the intensive care unit (ICU) depend on complex patterns in patients' longitudinal data. We aim to anticipate these events earlier and more consistently so that staff can consider preemptive action.
Critical Care Middle Aged Hospital Mortality Logistic Models Aged Neural Networks, Computer Aged, 80 and over Machine Learning Male Female Computer Simulation Humans Hospitalization Prognosis Intensive Care Units
View on PubMed DOI

Acceptability and Perceived Utility of Telemedical Consultation during Cardiac Arrest Resuscitation. A Multicenter Survey.

Annals of the American Thoracic Society Mar 1, 2020
Many clinicians who participate in or lead in-hospital cardiac arrest (IHCA) resuscitations lack confidence for this task or worry about errors. Well-led IHCA resuscitation teams deliver better care, but expert resuscitation leaders are often unavai...
Attitude of Health Personnel Hospital Units Humans Adult Idaho Telemedicine Heart Arrest Intensive Care Units Utah Male Medical Staff, Hospital Referral and Consultation Nursing Staff, Hospital Female Cardiopulmonary Resuscitation Middle Aged
View on PubMed DOI

Comment on "Utilizing Machine Learning Methods for Preoperative Prediction of Postsurgical Mortality and Intensive Care Unit Admission".

Annals of surgery Dec 1, 2019
Humans Machine Learning Intensive Care Units Hospitalization
View on PubMed DOI

Response to Comment on "Utilizing Machine Learning Methods for Preoperative Prediction of Postsurgical Mortality and Intensive Care Unit Admission".

Annals of surgery Dec 1, 2019
Hospitalization Humans Machine Learning Intensive Care Units
View on PubMed DOI
Popular Topics
Recent Journals