AIMC Topic: Vital Signs

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Early short-term prediction of emergency department length of stay using natural language processing for low-acuity outpatients.

The American journal of emergency medicine Mar 10, 2020
BACKGROUND: Low-acuity outpatients constitute the majority of emergency department (ED) patients, and these patients often experience an unpredictable length of stay (LOS). Effective LOS prediction might improve the quality of ED care and reduce ED c...
Humans Retrospective Studies Female Aged Adult Emergency Service, Hospital Patient Acuity Vital Signs Outpatients Crowding Clinical Decision Rules Male Middle Aged Length of Stay Taiwan Natural Language Processing
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Multi-Modal Diagnosis of Infectious Diseases in the Developing World.

IEEE journal of biomedical and health informatics Jan 9, 2020
In low and middle income countries, infectious diseases continue to have a significant impact, particularly amongst the poorest in society. Tetanus and hand foot and mouth disease (HFMD) are two such diseases and, in both, death is associated with au...
Hand, Foot and Mouth Disease Monitoring, Physiologic Models, Statistical Developing Countries Tetanus Vital Signs Humans Algorithms Communicable Diseases Adult Infant Diagnosis, Computer-Assisted Deep Learning Wearable Electronic Devices Child, Preschool Photoplethysmography Electrocardiography
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Representation learning in intraoperative vital signs for heart failure risk prediction.

BMC medical informatics and decision making Dec 9, 2019
BACKGROUND: The probability of heart failure during the perioperative period is 2% on average and it is as high as 17% when accompanied by cardiovascular diseases in China. It has been the most significant cause of postoperative death of patients. Ho...
Neural Networks, Computer Machine Learning Sensitivity and Specificity Risk Assessment China Monitoring, Intraoperative Humans Intraoperative Complications Decision Trees Area Under Curve Heart Failure Risk Vital Signs
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Cardio-respiratory signal extraction from video camera data for continuous non-contact vital sign monitoring using deep learning.

Physiological measurement Dec 2, 2019
UNLABELLED: Non-contact vital sign monitoring enables the estimation of vital signs, such as heart rate, respiratory rate and oxygen saturation (SpO), by measuring subtle color changes on the skin surface using a video camera. For patients in a hospi...
Humans Neural Networks, Computer Female Infant, Newborn Male Heart Deep Learning Video Recording Image Processing, Computer-Assisted Automation Monitoring, Physiologic Infant, Premature Signal Processing, Computer-Assisted Respiration Skin Vital Signs
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EXTraction of EMR numerical data: an efficient and generalizable tool to EXTEND clinical research.

BMC medical informatics and decision making Nov 15, 2019
BACKGROUND: Electronic medical records (EMR) contain numerical data important for clinical outcomes research, such as vital signs and cardiac ejection fractions (EF), which tend to be embedded in narrative clinical notes. In current practice, this da...
Glycated Hemoglobin Creatinine Information Storage and Retrieval Vital Signs Humans Algorithms Electronic Health Records Sensitivity and Specificity Stroke Volume Natural Language Processing
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Machine Learning Models for Analysis of Vital Signs Dynamics: A Case for Sepsis Onset Prediction.

Journal of healthcare engineering Nov 3, 2019
OBJECTIVE: Achieving accurate prediction of sepsis detection moment based on bedside monitor data in the intensive care unit (ICU). A good clinical outcome is more probable when onset is suspected and treated on time, thus early insight of sepsis ons...
Vital Signs Male Middle Aged Female Case-Control Studies Humans Aged Adolescent Diagnosis, Computer-Assisted Machine Learning Aged, 80 and over Support Vector Machine Sepsis Software Young Adult Area Under Curve Algorithms Adult Models, Biological Intensive Care Units Early Diagnosis Analysis of Variance
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Machine learning for prediction of septic shock at initial triage in emergency department.

Journal of critical care Oct 22, 2019
BACKGROUND: We hypothesized utilizing machine learning (ML) algorithms for screening septic shock in ED would provide better accuracy than qSOFA or MEWS.
Humans Machine Learning Software Algorithms Prognosis Support Vector Machine Adult Triage Electronic Health Records Male Vital Signs Area Under Curve Republic of Korea Middle Aged Emergency Service, Hospital Female Sepsis Multivariate Analysis Aged Hospital Mortality Young Adult Shock, Septic
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Recurrent Neural Networks for Early Detection of Heart Failure From Longitudinal Electronic Health Record Data: Implications for Temporal Modeling With Respect to Time Before Diagnosis, Data Density, Data Quantity, and Data Type.

Circulation. Cardiovascular quality and outcomes Oct 15, 2019
BACKGROUND: We determined the impact of data volume and diversity and training conditions on recurrent neural network methods compared with traditional machine learning methods.
Early Diagnosis Smoking Alcohol Drinking California Vital Signs Time Factors Primary Health Care Longitudinal Studies Predictive Value of Tests Heart Failure Reproducibility of Results Risk Factors Male Diagnosis, Computer-Assisted Incidence Humans Neural Networks, Computer Machine Learning Electronic Health Records Female
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Combining patient visual timelines with deep learning to predict mortality.

PloS one Jul 31, 2019
BACKGROUND: Deep learning algorithms have achieved human-equivalent performance in image recognition. However, the majority of clinical data within electronic health records is inherently in a non-image format. Therefore, creating visual representati...
Intensive Care Units Electronic Health Records Female Hospitalization Male Middle Aged Humans Neural Networks, Computer Machine Learning Retrospective Studies Deep Learning Hospital Mortality ROC Curve Patient Admission Vital Signs
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An intelligent warning model for early prediction of cardiac arrest in sepsis patients.

Computer methods and programs in biomedicine Jun 11, 2019
BACKGROUND: Sepsis-associated cardiac arrest is a common issue with the low survival rate. Early prediction of cardiac arrest can provide the time required for intervening and preventing its onset in order to reduce mortality. Several studies have be...
Monitoring, Ambulatory APACHE Multivariate Analysis Vital Signs Normal Distribution Heart Arrest Humans Severity of Illness Index Young Adult Machine Learning Case-Control Studies Algorithms Adult Sepsis Electronic Health Records Sensitivity and Specificity Adolescent Female Male Incidence Reproducibility of Results Middle Aged Decision Trees
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