AIMC Topic: Vital Signs

Clear Filters Showing 21 to 30 of 96 articles

Prediction of Transfusion among In-patient Population using Temporal Pattern based Clinical Similarity Graphs.

AMIA ... Annual Symposium proceedings. AMIA Symposium Jan 11, 2024
Intelligent prediction of risk of blood transfusion among hospitalized patients can identify at-risk patients and provide timely information to the hospital to plan and reserve resources to meet the demand of blood transfusion. While previously propo...
Female Blood Transfusion Vital Signs Humans Neural Networks, Computer
View on PubMed

Weakly Supervised Classification of Vital Sign Alerts as Real or Artifact.

AMIA ... Annual Symposium proceedings. AMIA Symposium Apr 29, 2023
A significant proportion of clinical physiologic monitoring alarms are false. This often leads to alarm fatigue in clinical personnel, inevitably compromising patient safety. To combat this issue, researchers have attempted to build Machine Learning ...
Vital Signs Artifacts Automation Humans Monitoring, Physiologic Supervised Machine Learning Heuristics
View on PubMed

Effectiveness of mobile robots collecting vital signs and radiation dose rate for patients receiving Iodine-131 radiotherapy: A randomized clinical trial.

Frontiers in public health Jan 9, 2023
OBJECTIVE: Patients receiving radionuclide 131I treatment expose radiation to others, and there was no clinical trial to verify the effectiveness and safety of mobile robots in radionuclide 131I isolation wards. The objective of this randomized clini...
Female Adult Male China Humans Radiation Dosage Robotics Vital Signs Iodine Radioisotopes
View on PubMed DOI

Development of a machine learning model for the prediction of the short-term mortality in patients in the intensive care unit.

Journal of critical care Jul 11, 2022
PURPOSE: The aim of this study was to develop and evaluate a machine learning model that predicts short-term mortality in the intensive care unit using the trends of four easy-to-collect vital signs.
Area Under Curve Vital Signs Intensive Care Units ROC Curve Humans Machine Learning
View on PubMed DOI

Prediction of serious outcomes based on continuous vital sign monitoring of high-risk patients.

Computers in biology and medicine May 18, 2022
Continuous monitoring of high-risk patients and early prediction of severe outcomes is crucial to prevent avoidable deaths. Current clinical monitoring is primarily based on intermittent observation of vital signs and the early warning scores (EWS). ...
Machine Learning ROC Curve Humans Oximetry Area Under Curve Vital Signs
View on PubMed DOI

Camera fusion for real-time temperature monitoring of neonates using deep learning.

Medical & biological engineering & computing May 3, 2022
The continuous monitoring of vital signs is a crucial aspect of medical care in neonatal intensive care units. Since cable-based sensors pose a potential risk for the immature skin of preterm infants, unobtrusive monitoring techniques using camera sy...
Humans Infant, Newborn Vital Signs Thermography Deep Learning Infant, Premature Temperature Infant
View on PubMed DOI

Development and External Validation of a Machine Learning Model for Prediction of Potential Transfer to the PICU.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Apr 21, 2022
OBJECTIVES: Unrecognized clinical deterioration during illness requiring hospitalization is associated with high risk of mortality and long-term morbidity among children. Our objective was to develop and externally validate machine learning algorithm...
Vital Signs Child Intensive Care Units, Pediatric Humans Machine Learning Electronic Health Records Cohort Studies Retrospective Studies
View on PubMed DOI

Fusion of fully integrated analog machine learning classifier with electronic medical records for real-time prediction of sepsis onset.

Scientific reports Apr 5, 2022
The objective of this work is to develop a fusion artificial intelligence (AI) model that combines patient electronic medical record (EMR) and physiological sensor data to accurately predict early risk of sepsis. The fusion AI model has two component...
Vital Signs Artificial Intelligence Machine Learning Electronic Health Records Sepsis Humans
View on PubMed DOI

A Machine-Learning-Based System for Prediction of Cardiovascular and Chronic Respiratory Diseases.

Journal of healthcare engineering Nov 1, 2021
Cardiovascular and chronic respiratory diseases are global threats to public health and cause approximately 19 million deaths worldwide annually. This high mortality rate can be reduced with the use of technological advancements in medical science th...
Bayes Theorem Algorithms Humans Vital Signs Support Vector Machine Machine Learning
View on PubMed DOI

AIOSA: An approach to the automatic identification of obstructive sleep apnea events based on deep learning.

Artificial intelligence in medicine Jul 2, 2021
Obstructive Sleep Apnea Syndrome (OSAS) is the most common sleep-related breathing disorder. It is caused by an increased upper airway resistance during sleep, which determines episodes of partial or complete interruption of airflow. The detection an...
Vital Signs Polysomnography Sleep Apnea, Obstructive Sleep Humans Deep Learning
View on PubMed DOI
Popular Topics
Recent Journals