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Critical Care

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Toward the "Plateau of Productivity": Enhancing the Value of Machine Learning in Critical Care.

Critical care medicine Jul 1, 2018
Humans Machine Learning Algorithms Intensive Care Units Critical Care
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Applying Machine Learning to Pediatric Critical Care Data.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies Jul 1, 2018
OBJECTIVES: To explore whether machine learning applied to pediatric critical care data could discover medically pertinent information, we analyzed clinically collected electronic medical record data, after data extraction and preparation, using k-me...
Electronic Health Records Intensive Care Units, Pediatric Machine Learning Critical Care Information Dissemination
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Mortality Prediction Gets a "Boost".

Critical care medicine Jun 1, 2018
Hospital Mortality Critical Care Risk Adjustment Machine Learning Algorithms Humans
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[Application of support vector machine in predicting in-hospital mortality risk of patients with acute kidney injury in ICU].

Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences Apr 18, 2018
OBJECTIVE: To construct an in-hospital mortality prediction model for patients with acute kidney injury (AKI) in intensive care unit (ICU) by using support vector machine (SVM), and compare it with the simplified acute physiology score II (SAPS-II) w...
Hospital Mortality Acute Kidney Injury ROC Curve Support Vector Machine Intensive Care Units Sensitivity and Specificity Critical Care Humans Prognosis
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Learning Healthcare Systems in Pediatrics: Cross-Institutional and Data-Driven Decision-Support for Intensive Care Environments (CADDIE).

Studies in health technology and informatics Jan 1, 2018
BACKGROUND: The vast amount of data generated in healthcare can be reused to support decision-making by developing clinical decision-support systems. Since evidence is lacking in Pediatrics, it seems to be beneficial to design future systems towards ...
Pediatrics Decision Support Systems, Clinical Data Collection Critical Care Humans Machine Learning Algorithms Child Intensive Care Units, Pediatric
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Benefit of Critical Care Flight Paramedic-Trained Search and Rescue Corpsmen in Treatment of Severely Injured Aviators.

Journal of special operations medicine : a peer reviewed journal for SOF medical professionals Jan 1, 2018
During routine aircraft start-up procedures at a US Naval Air Station, an aviation mishap occurred, resulting in the pilot suffering a traumatic brain injury and the copilot acquiring bilateral hemopneumothoraces, a ruptured diaphragm, and hepatic an...
Hemothorax Naval Medicine Rescue Work Liver Multiple Trauma Air Ambulances Rupture Male Contusions Middle Aged Humans Critical Care Brain Injuries, Traumatic Diaphragm Military Personnel Spleen Emergency Medical Technicians
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Mapping Patient Trajectories using Longitudinal Extraction and Deep Learning in the MIMIC-III Critical Care Database.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2018
Electronic Health Records (EHRs) contain a wealth of patient data useful to biomedical researchers. At present, both the extraction of data and methods for analyses are frequently designed to work with a single snapshot of a patient's record. Health ...
Humans Machine Learning Male Computational Biology Unsupervised Machine Learning Supervised Machine Learning Databases, Factual Electronic Health Records Female Critical Care
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Extracorporeal membrane oxygenation combined with continuous renal replacement therapy in cutaneous burn and inhalation injury caused by hydrofluoric acid and nitric acid.

Medicine Dec 1, 2017
RATIONALE: Hydrofluoric acid (HF) is a highly corrosive agent and can cause corrosive burns. HF can penetrate deeply into tissues through intact skin and the lipid barrier, leading to painful liquefactive necrosis, and inducing hypocalcemia and hypom...
Extracorporeal Membrane Oxygenation Adult Humans Male Critical Care Hydrofluoric Acid Burns, Chemical Anti-Bacterial Agents Nitric Acid Skin Transplantation Renal Replacement Therapy
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Identifying Distinct Subgroups of ICU Patients: A Machine Learning Approach.

Critical care medicine Oct 1, 2017
OBJECTIVES: Identifying subgroups of ICU patients with similar clinical needs and trajectories may provide a framework for more efficient ICU care through the design of care platforms tailored around patients' shared needs. However, objective methods...
Needs Assessment Cluster Analysis Critical Care California Aged Male Middle Aged Intensive Care Units Humans Female Machine Learning
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Visualizing patient journals by combining vital signs monitoring and natural language processing.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Aug 1, 2016
This paper presents a data-driven approach to graphically presenting text-based patient journals while still maintaining all textual information. The system first creates a timeline representation of a patients' physiological condition during an admi...
Aged Middle Aged Hospitals Models, Statistical Patient Admission Denmark Vital Signs Humans Sepsis Heart Arrest Respiratory Insufficiency Monitoring, Physiologic Natural Language Processing Critical Care Intensive Care Units Blood Pressure Medical Informatics Hospitalization Oxygen
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