AIMC Topic: Vital Signs

Clear Filters Showing 51 to 60 of 92 articles

An Algorithm Based on Deep Learning for Predicting In-Hospital Cardiac Arrest.

Journal of the American Heart Association Jun 26, 2018
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 arrest early, they have limitations, with low sensitivity and high fal...
Resuscitation Seoul Time Factors Inpatients Predictive Value of Tests Early Diagnosis Vital Signs Heart Arrest Prognosis Retrospective Studies Female Reproducibility of Results Risk Factors Aged Adult Male Middle Aged Risk Assessment Diagnosis, Computer-Assisted Deep Learning Humans Decision Support Techniques
View on PubMed DOI

Internet of Health Things: Toward intelligent vital signs monitoring in hospital wards.

Artificial intelligence in medicine Jun 2, 2018
BACKGROUND: Large amounts of patient data are routinely manually collected in hospitals by using standalone medical devices, including vital signs. Such data is sometimes stored in spreadsheets, not forming part of patients' electronic health records...
Humans Artificial Intelligence Machine Learning Prognosis Monitoring, Ambulatory Medical Record Linkage Vital Signs Clinical Alarms Hospital Units Wireless Technology Electronic Health Records Health Status Patient-Centered Care Internet Data Mining Telemedicine
View on PubMed DOI

ProFUSO: Business process and ontology-based framework to develop ubiquitous computing support systems for chronic patients' management.

Journal of biomedical informatics Apr 5, 2018
New advances in telemedicine, ubiquitous computing, and artificial intelligence have supported the emergence of more advanced applications and support systems for chronic patients. This trend addresses the important problem of chronic illnesses, high...
Humans Artificial Intelligence Hospitalization Semantics Vital Signs Models, Organizational Computer Graphics Decision Support Systems, Clinical Decision Making Chronic Disease Telemedicine Information Storage and Retrieval Medical Informatics
View on PubMed DOI

Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU.

BMJ open Jan 26, 2018
OBJECTIVES: We validate a machine learning-based sepsis-prediction algorithm () for the detection and prediction of three sepsis-related gold standards, using only six vital signs. We evaluate robustness to missing data, customisation to site-specifi...
Male Middle Aged Severity of Illness Index Length of Stay Sepsis Adolescent Retrospective Studies Intensive Care Units Female Aged Young Adult Adult San Francisco Boston Patients' Rooms Hospital Mortality ROC Curve Shock, Septic Area Under Curve Emergency Service, Hospital Vital Signs Humans Machine Learning Algorithms Databases, Factual Prognosis
View on PubMed DOI

Machine-Learning-Based Electronic Triage More Accurately Differentiates Patients With Respect to Clinical Outcomes Compared With the Emergency Severity Index.

Annals of emergency medicine Sep 6, 2017
STUDY OBJECTIVE: Standards for emergency department (ED) triage in the United States rely heavily on subjective assessment and are limited in their ability to risk-stratify patients. This study seeks to evaluate an electronic triage system (e-triage)...
Cross-Sectional Studies Male United States Triage Area Under Curve Emergency Service, Hospital Vital Signs Humans Machine Learning Algorithms Retrospective Studies Female Adult
View on PubMed DOI

Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks.

Methods of information in medicine Aug 16, 2017
OBJECTIVE: To describe and compare logistic regression and neural network modeling strategies to predict hospital admission or transfer following initial presentation to Emergency Department (ED) triage with and without the addition of natural langua...
Humans ROC Curve Neural Networks, Computer Models, Theoretical Female Natural Language Processing Aged Hospitalization Emergency Service, Hospital Young Adult Vital Signs Adult Male Middle Aged Adolescent
View on PubMed DOI

A Model-Based Machine Learning Approach to Probing Autonomic Regulation From Nonstationary Vital-Sign Time Series.

IEEE journal of biomedical and health informatics Dec 7, 2016
Physiological variables, such as heart rate (HR), blood pressure (BP) and respiration (RESP), are tightly regulated and coupled under healthy conditions, and a break-down in the coupling has been associated with aging and disease. We present an appro...
Humans Machine Learning Algorithms Databases, Factual Female Aged Aged, 80 and over Sepsis Young Adult Baroreflex Adult Monitoring, Physiologic Male Models, Statistical Aging Area Under Curve Middle Aged Signal Processing, Computer-Assisted Critical Care Vital Signs
View on PubMed DOI

Prediction of Clinical Deterioration in Hospitalized Adult Patients with Hematologic Malignancies Using a Neural Network Model.

PloS one Aug 17, 2016
INTRODUCTION: Clinical deterioration (ICU transfer and cardiac arrest) occurs during approximately 5-10% of hospital admissions. Existing prediction models have a high false positive rate, leading to multiple false alarms and alarm fatigue. We used r...
Treatment Outcome Monitoring, Physiologic Critical Care Early Diagnosis Vital Signs Heart Arrest Hematologic Neoplasms Male Neural Networks, Computer Middle Aged Machine Learning Adolescent Algorithms Cohort Studies Prognosis Models, Theoretical Retrospective Studies Female Electronic Health Records Aged Aged, 80 and over Young Adult Humans Adult
View on PubMed DOI

Real alerts and artifact classification in archived multi-signal vital sign monitoring data: implications for mining big data.

Journal of clinical monitoring and computing Oct 5, 2015
Huge hospital information system databases can be mined for knowledge discovery and decision support, but artifact in stored non-invasive vital sign (VS) high-frequency data streams limits its use. We used machine-learning (ML) algorithms trained on ...
Area Under Curve Data Interpretation, Statistical Data Mining Heart Rate Adult Artifacts Male Risk Middle Aged Humans Vital Signs Decision Support Systems, Clinical Hospital Information Systems Machine Learning Monitoring, Physiologic Oscillometry Algorithms Blood Pressure Clinical Alarms Female Aged
View on PubMed DOI

Clinical evaluation of the newly developed infectious disease/fever screening radar system using the neural network and fuzzy grouping method for travellers with suspected infectious diseases at Narita International Airport Clinic.

The Journal of infection Sep 28, 2015
Middle Aged Adolescent Mass Screening Fuzzy Logic Humans Vital Signs Algorithms Cluster Analysis Neural Networks, Computer Communicable Disease Control Fever Female Radar Aged Travel Young Adult Airports Adult Male
View on PubMed DOI
Popular Topics
Recent Journals