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Critical Care

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An empirical evaluation of deep learning for ICD-9 code assignment using MIMIC-III clinical notes.

Computer methods and programs in biomedicine May 25, 2019
BACKGROUND AND OBJECTIVE: Code assignment is of paramount importance in many levels in modern hospitals, from ensuring accurate billing process to creating a valid record of patient care history. However, the coding process is tedious and subjective,...
Deep Learning Models, Statistical Regression Analysis Critical Care Intensive Care Units Electronic Health Records Reproducibility of Results Medical Informatics International Classification of Diseases Humans Neural Networks, Computer Algorithms
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Is artificial intelligence (AI) at the doorstep of Intensive Care Units (ICU) and operating room (OR)?

Anaesthesia, critical care & pain medicine May 15, 2019
Intensive Care Units Critical Care Intraoperative Care Operating Rooms Humans Artificial Intelligence
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A machine learning approach for predicting urine output after fluid administration.

Computer methods and programs in biomedicine May 13, 2019
BACKGROUND AND OBJECTIVE: To develop a machine learning model to predict urine output (UO) in sepsis patients after fluid resuscitation.
Intensive Care Units Electronic Health Records Female Risk Factors Humans Machine Learning Algorithms Area Under Curve Fluid Therapy Middle Aged Critical Care Sepsis Aged Urination Decision Support Systems, Clinical Sensitivity and Specificity Kidney Function Tests Male Resuscitation
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Analysis of parameters affecting blood oxygen saturation and modeling of fuzzy logic system for inspired oxygen prediction.

Computer methods and programs in biomedicine Apr 30, 2019
BACKGROUND AND OBJECTIVE: Fraction of Inspired Oxygen is one of the arbitrary set ventilator parameters which has critical influence on the concentration of blood oxygen. Normally mechanical ventilators providing respiratory assistance are tuned manu...
Pulmonary Gas Exchange Oximetry Decision Making Oxygen Critical Care Therapy, Computer-Assisted Respiration, Artificial Decision Support Systems, Clinical Fuzzy Logic Machine Learning Humans Software Intensive Care Units Reproducibility of Results
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Inverse reinforcement learning for intelligent mechanical ventilation and sedative dosing in intensive care units.

BMC medical informatics and decision making Apr 9, 2019
BACKGROUND: Reinforcement learning (RL) provides a promising technique to solve complex sequential decision making problems in health care domains. To ensure such applications, an explicit reward function encoding domain knowledge should be specified...
Clinical Protocols Humans Critical Care Machine Learning Markov Chains Retrospective Studies Reinforcement, Psychology Clinical Decision-Making Respiration, Artificial Hypnotics and Sedatives Bayes Theorem
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Machine learning for the prediction of volume responsiveness in patients with oliguric acute kidney injury in critical care.

Critical care (London, England) Apr 8, 2019
BACKGROUND AND OBJECTIVES: Excess fluid balance in acute kidney injury (AKI) may be harmful, and conversely, some patients may respond to fluid challenges. This study aimed to develop a prediction model that can be used to differentiate between volum...
Humans Acute Kidney Injury Oliguria Machine Learning Time Factors Intensive Care Units Aged, 80 and over Logistic Models Female Male Fluid Therapy Aged Critical Care Middle Aged
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Machine learning applied to multi-sensor information to reduce false alarm rate in the ICU.

Journal of clinical monitoring and computing Apr 6, 2019
Studies reveal that the false alarm rate (FAR) demonstrated by intensive care unit (ICU) vital signs monitors ranges from 0.72 to 0.99. We applied machine learning (ML) to ICU multi-sensor information to imitate a medical specialist in diagnosing pat...
Clinical Alarms Retrospective Studies Intensive Care Units Monitoring, Physiologic Humans Knowledge Bases Critical Care Machine Learning Decision Support Techniques Expert Systems Pattern Recognition, Automated False Positive Reactions
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Enabling artificial intelligence in high acuity medical environments.

Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy Apr 5, 2019
Acute patient treatment can heavily profit from AI-based assistive and decision support systems, in terms of improved patient outcome as well as increased efficiency. Yet, only very few applications have been reported because of the limited accessibi...
Decision Support Systems, Clinical Workflow Critical Care Efficiency, Organizational Humans Artificial Intelligence Surgical Procedures, Operative
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Towards a decision support tool for intensive care discharge: machine learning algorithm development using electronic healthcare data from MIMIC-III and Bristol, UK.

BMJ open Mar 7, 2019
OBJECTIVE: The primary objective is to develop an automated method for detecting patients that are ready for discharge from intensive care.
Algorithms Female Humans Patient Discharge Male Machine Learning Critical Care Decision Support Techniques England Patient Readmission Electronic Health Records Length of Stay
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Machine learning models for early sepsis recognition in the neonatal intensive care unit using readily available electronic health record data.

PloS one Feb 22, 2019
BACKGROUND: Rapid antibiotic administration is known to improve sepsis outcomes, however early diagnosis remains challenging due to complex presentation. Our objective was to develop a model using readily available electronic health record (EHR) data...
Infant Diagnosis, Computer-Assisted Sepsis Electronic Health Records Models, Biological Female Humans Critical Care Infant, Newborn Machine Learning Male Retrospective Studies
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