AIMC Topic: Blood Pressure Determination

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[Noninvasive Continuous Blood Pressure Measurement Method Based on EEMD and ANN].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation Jul 30, 2017
Blood pressure is an important index to measure the function of human cardiovascular system. In order to solve the problem of non-invasive continuous measurement of blood pressure in electronic sphygmomanometer, a noninvasive blood pressure measureme...
Humans Neural Networks, Computer Heart Rate Cardiovascular System Blood Pressure Determination Blood Pressure
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P673Improvement of arterial stiffness and myocardial deformation in patients with poorly controlled diabetes mellitus type 2 after optimization of antidiabetic medication.

European heart journal. Cardiovascular Imaging Dec 1, 2016
BACKGROUND: Arterial stiffness is associated with increased risk for cardiovascular disease. The purpose of this study is to investigate the arterial stiffness and myocardial deformation in patients with poorly controlled diabetes mellitus type 2 bef...
Ventricular Dysfunction, Left Carotid Intima-Media Thickness Blood Glucose Male Hemodynamic Monitoring Diabetes Mellitus, Type 2 Middle Aged Case-Control Studies Female Pulse Wave Analysis Risk Assessment Treatment Outcome Adult Follow-Up Studies Reference Values Severity of Illness Index Vascular Stiffness Humans Blood Pressure Determination Hypoglycemic Agents
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Using Supervised Machine Learning to Classify Real Alerts and Artifact in Online Multisignal Vital Sign Monitoring Data.

Critical care medicine Jul 1, 2016
OBJECTIVE: The use of machine-learning algorithms to classify alerts as real or artifacts in online noninvasive vital sign data streams to reduce alarm fatigue and missed true instability.
Cohort Studies Blood Pressure Determination Humans Oximetry Artifacts Vital Signs Respiratory Rate Clinical Alarms Supervised Machine Learning Heart Rate Monitoring, Physiologic
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Blood pressure and heart rate from the arterial blood pressure waveform can reliably estimate cardiac output in a conscious sheep model of multiple hemorrhages and resuscitation using computer machine learning approaches.

The journal of trauma and acute care surgery Oct 1, 2015
BACKGROUND: This study was a first step to facilitate the development of automated decision support systems using cardiac output (CO) for combat casualty care. Such systems remain a practical challenge in battlefield and prehospital settings. In thes...
Resuscitation Traumatology Sheep, Domestic Military Medicine Hemorrhage Machine Learning Arterial Pressure Calibration Animals Cardiac Output Hemodynamics Pulse Wave Analysis Blood Pressure Determination Disease Models, Animal Heart Rate Decision Support Techniques Predictive Value of Tests Algorithms Female
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