| review article | Q7318358 |
| scholarly article | Q13442814 |
| P356 | DOI | 10.1038/NRNEUROL.2011.101 |
| P8608 | Fatcat ID | release_4vijwoz3jnh2zgw35qm2ghxfey |
| P698 | PubMed publication ID | 21750522 |
| P2093 | author name string | J Claude Hemphill | |
| Peter Andrews | |||
| Michael De Georgia | |||
| P2860 | cites work | Modelling biological complexity: a physical scientist's perspective | Q22065949 |
| Routine intracranial pressure monitoring in acute coma | Q24239972 | ||
| Multiparameter Intelligent Monitoring in Intensive Care II: a public-access intensive care unit database | Q28743230 | ||
| Physiological time-series analysis using approximate entropy and sample entropy | Q30305723 | ||
| Sample entropy analysis of neonatal heart rate variability | Q30309844 | ||
| Predicting recovery in patients suffering from traumatic brain injury by using admission variables and physiological data: a comparison between decision tree analysis and logistic regression | Q30714667 | ||
| Physiologic data acquisition system and database for the study of disease dynamics in the intensive care unit | Q30767954 | ||
| From inverse problems in mathematical physiology to quantitative differential diagnoses | Q30837875 | ||
| ICM+: software for on-line analysis of bedside monitoring data after severe head trauma | Q31031936 | ||
| Multimodal monitoring in the neurological intensive care unit | Q31138825 | ||
| Toward optimal display of physiologic status in critical care: I. Recreating bedside displays from archived physiologic data | Q33683062 | ||
| Noninvasive measurement of cerebral blood flow and blood oxygenation using near-infrared and diffuse correlation spectroscopies in critically brain-injured adults | Q33749266 | ||
| Identification of complex metabolic states in critically injured patients using bioinformatic cluster analysis | Q33873415 | ||
| Continuous monitoring of cerebrovascular pressure reactivity allows determination of optimal cerebral perfusion pressure in patients with traumatic brain injury | Q34122795 | ||
| Decreased heart rate variability and its association with increased mortality after acute myocardial infarction | Q34191387 | ||
| Treatment of fever in the neurologic intensive care unit with a catheter-based heat exchange system. | Q34294389 | ||
| Prevention of secondary ischemic insults after severe head injury. | Q34505580 | ||
| Current concepts in neurocritical care | Q34776008 | ||
| Camino intracranial pressure monitor: prospective study of accuracy and complications | Q35457816 | ||
| Increased jugular bulb saturation is associated with poor outcome in traumatic brain injury | Q35572276 | ||
| Guidelines for the management of spontaneous intracerebral hemorrhage: a guideline for healthcare professionals from the American Heart Association/American Stroke Association | Q35711431 | ||
| Critical care management of acute ischemic stroke | Q35742584 | ||
| Nonlinear dynamics, complex systems, and the pathobiology of critical illness. | Q35896086 | ||
| Consensus meeting on microdialysis in neurointensive care | Q35953234 | ||
| Continuous monitoring of the microcirculation in neurocritical care: an update on brain tissue oxygenation | Q36423815 | ||
| Microdialysis: is it ready for prime time? | Q36670678 | ||
| The Effect of Decompressive Hemicraniectomy on Brain Temperature After Severe Brain Injury | Q36767868 | ||
| Multimodality monitoring in neurocritical care | Q36953769 | ||
| NICEM consensus on neurological monitoring in acute neurological disease. | Q37132806 | ||
| Detrended fluctuation analysis of intracranial pressure predicts outcome following traumatic brain injury | Q37317220 | ||
| Hyperthermia and fever control in brain injury | Q37523048 | ||
| Intracranial multimodal monitoring for acute brain injury: a single institution review of current practices | Q37682677 | ||
| The brain monitoring with Information Technology (BrainIT) collaborative network: EC feasibility study results and future direction | Q38428768 | ||
| Using hierarchical dynamic Bayesian networks to investigate dynamics of organ failure in patients in the Intensive Care Unit | Q39934341 | ||
| Development of a multimodal monitoring platform for medical research | Q39959927 | ||
| BrainIT: a trans-national head injury monitoring research network. | Q40328620 | ||
| Cerebral microdialysis of patients with severe traumatic brain injury exhibits highly individualistic patterns as visualized by cluster analysis with self-organizing maps. | Q40461011 | ||
| Brain temperature exceeds systemic temperature in head-injured patients | Q40640825 | ||
| SjvO2 monitoring in head-injured patients | Q40679242 | ||
| Continuous monitoring of regional cerebral blood flow during temporary arterial occlusion in aneurysm surgery | Q40685501 | ||
| Classes of tissue hypoxia. | Q40690380 | ||
| Brain oxygen tension in severe head injury | Q40769859 | ||
| Uncoupling of biological oscillators: a complementary hypothesis concerning the pathogenesis of multiple organ dysfunction syndrome | Q41010995 | ||
| Neurological intensive care | Q41106337 | ||
| Novel representation of physiologic states during critical illness and recovery | Q41128389 | ||
| Cerebral perfusion pressure and brain ischaemia: can one size fit all? | Q42120564 | ||
| The digital patient: predicting physiologic dynamics with mathematical models | Q43652103 | ||
| Prognostic value of heart rate variability in chronic congestive heart failure secondary to idiopathic or ischemic dilated cardiomyopathy | Q44203081 | ||
| Linear and nonlinear analysis of heart rate variability during propofol anesthesia for short-duration procedures in children. | Q44494566 | ||
| BrainIT collaborative network: analyses from a high time-resolution dataset of head injured patients | Q44754811 | ||
| Brain tissue oxygen monitoring in intracerebral hemorrhage | Q45163987 | ||
| Persistent metabolic crisis as measured by elevated cerebral microdialysis lactate-pyruvate ratio predicts chronic frontal lobe brain atrophy after traumatic brain injury | Q45386677 | ||
| Impaired cerebral vasomotor activity in spontaneous intracerebral hemorrhage | Q46182133 | ||
| Insulin therapy protects the central and peripheral nervous system of intensive care patients | Q46455443 | ||
| New approaches to physiological informatics in neurocritical care | Q46643295 | ||
| Inflammation in human brain injury: intracerebral concentrations of IL-1alpha, IL-1beta, and their endogenous inhibitor IL-1ra | Q46923745 | ||
| Regional cerebral blood flow monitoring in the diagnosis of delayed ischemia following aneurysmal subarachnoid hemorrhage | Q47818190 | ||
| The checklist: if something so simple can transform intensive care, what else can it do? | Q48022760 | ||
| Intracortical EEG for the detection of vasospasm in patients with poor-grade subarachnoid hemorrhage | Q48116063 | ||
| Guidelines for the management of severe traumatic brain injury. IX. Cerebral perfusion thresholds | Q48163493 | ||
| Guidelines for the management of severe traumatic brain injury. VIII. Intracranial pressure thresholds | Q48163500 | ||
| Guidelines for the management of severe traumatic brain injury. VII. Intracranial pressure monitoring technology | Q48163505 | ||
| Merits and pitfalls of multimodality brain monitoring | Q48237749 | ||
| The role of secondary brain injury in determining outcome from severe head injury | Q48335021 | ||
| Estimation of the main factors affecting ICP dynamics by mathematical analysis of PVI tests. | Q48372300 | ||
| Clinical implications of quantitative infrared pupillometry in neurosurgical patients | Q48425835 | ||
| Prognostic significance of continuous EEG monitoring in patients with poor-grade subarachnoid hemorrhage | Q48504182 | ||
| Interpretation of approximate entropy: analysis of intracranial pressure approximate entropy during acute intracranial hypertension | Q48724298 | ||
| Pressure reactivity as a guide in the treatment of cerebral perfusion pressure in patients with brain trauma | Q48987187 | ||
| Addressing the flaws of current critical alarms: a fuzzy constraint satisfaction approach. | Q49012157 | ||
| Quantitative continuous EEG for detecting delayed cerebral ischemia in patients with poor-grade subarachnoid hemorrhage. | Q51984138 | ||
| Discussing anomalous situations using decision trees: a head injury case study. | Q52048971 | ||
| Prognostic significance of advanced neuromonitoring after traumatic brain injury using neural networks. | Q52077310 | ||
| Continuous regional cerebral cortical blood flow monitoring in head-injured patients. | Q53643797 | ||
| Overcoming barriers to electronic medical record (EMR) implementation in the US healthcare system: A comparative study | Q56905166 | ||
| Physiologic Stability and Physiologic State | Q57773667 | ||
| Altered Complexity and Correlation Properties of R-R Interval Dynamics Before the Spontaneous Onset of Paroxysmal Atrial Fibrillation | Q57914844 | ||
| Data Acquisition and Complex Systems Analysis in Critical Care: Developing the Intensive Care Unit of the Future | Q57978897 | ||
| Investigation of altered heart rate variability, nonlinear properties of heart rate signals, and organ dysfunction longitudinally over time in intensive care unit patients | Q61501266 | ||
| Spectral analysis of fluctuations in heart rate: an objective evaluation of autonomic nervous control in chronic renal failure | Q69000474 | ||
| Mild hypovolemic stress alters autonomic modulation of heart rate | Q70550102 | ||
| Cerebral perfusion pressure: management protocol and clinical results | Q71566310 | ||
| Cerebral blood flow (CBF) monitoring in intensive care by thermal diffusion | Q72779607 | ||
| Gender- and age-related differences in heart rate dynamics: are women more complex than men? | Q72811854 | ||
| Effect of intra-arterial papaverine on regional cerebral blood flow in hemodynamically relevant cerebral vasospasm | Q73395994 | ||
| Depressed heart rate variability is associated with events in patients with stable coronary artery disease and preserved left ventricular function. REGRESS Study Group | Q74434197 | ||
| Heart rate variability and its determinants in patients with severe or mild essential hypertension | Q74566308 | ||
| Computers in the intensive care unit: promises yet to be fulfilled | Q77067724 | ||
| The Camino intracranial pressure device in clinical practice: reliability, handling characteristics and complications | Q77739713 | ||
| Intracranial pressure. Part one: historical overview and basic concepts | Q80312339 | ||
| Intracranial pressure. Part two: Clinical applications and technology | Q80312343 | ||
| Intracranial pressure variability and long-term outcome following traumatic brain injury | Q83708071 | ||
| Electronic medical record and quality of patient care in the VA | Q84247605 | ||
| P433 | issue | 8 | |
| P407 | language of work or name | English | Q1860 |
| P921 | main subject | bioinformatics | Q128570 |
| P304 | page(s) | 451-460 | |
| P577 | publication date | 2011-07-12 | |
| P1433 | published in | Nature Reviews Neurology | Q2079285 |
| P1476 | title | Multimodal monitoring and neurocritical care bioinformatics | |
| P478 | volume | 7 |
| Q38625528 | "Usability of data integration and visualization software for multidisciplinary pediatric intensive care: a human factors approach to assessing technology". |
| Q28816918 | A review of flux considerations for in vivo neurochemical measurements |
| Q49525603 | Advances in neurosurgery: Five new things |
| Q38430484 | Alternative clinical trial design in neurocritical care |
| Q38079720 | Analysis of intracranial pressure: past, present, and future. |
| Q26823369 | Bench-to-Bedside and Bedside Back to the Bench; Seeking a Better Understanding of the Acute Pathophysiological Process in Severe Traumatic Brain Injury |
| Q26800999 | Big Data Analytics in Healthcare |
| Q62496796 | Big Data in traumatic brain injury; promise and challenges |
| Q92829698 | Big data in status epilepticus |
| Q38226177 | Brain tissue oxygenation, lactate-pyruvate ratio, and cerebrovascular pressure reactivity monitoring in severe traumatic brain injury: systematic review and viewpoint |
| Q90319422 | Cerebral Vascular Changes During Acute Intracranial Pressure Drop |
| Q98164744 | Current Status and Recommendations in Multimodal Neuromonitoring |
| Q30924720 | Data collection and interpretation. |
| Q37716250 | Does heart rate variability reflect the systemic inflammatory response in a fetal sheep model of lipopolysaccharide-induced sepsis? |
| Q36428139 | Dynamics of endogenous Hsp70 synthesis in the brain of olfactory bulbectomized mice |
| Q31027257 | Editorial: Perinatology in the Era of Big Data and Nanoparticles |
| Q28687109 | Emerging subspecialties: neuroinformatics |
| Q38229015 | Finding an optimal rehabilitation paradigm after stroke: enhancing fiber growth and training of the brain at the right moment |
| Q38903003 | Guiding Principles for a Pediatric Neurology ICU (neuroPICU) Bedside Multimodal Monitor: Findings from an International Working Group. |
| Q48106463 | Impact of extended monitoring-guided intensive care on outcome after severe traumatic brain injury: A prospective multicentre cohort study (PariS-TBI study). |
| Q38123981 | Informatics for neurocritical care: challenges and opportunities |
| Q41919116 | Insulin-associated neuroinflammatory pathways as therapeutic targets for traumatic brain injury |
| Q34439961 | Introducing a nationwide registry: the Swiss study on aneurysmal subarachnoid haemorrhage (Swiss SOS). |
| Q54341785 | Is C-reactive protein useful as a predictor for poor outcome after aneurysmal subarachnoid hemorrhage? |
| Q27004377 | Multimodality monitoring in the neurointensive care unit: a special perspective for patients with stroke |
| Q87354355 | Neurocritical care in Germany: need for guidance |
| Q38074833 | Physiological monitoring of the severe traumatic brain injury patient in the intensive care unit |
| Q38851692 | Predicting Intracranial Pressure and Brain Tissue Oxygen Crises in Patients With Severe Traumatic Brain Injury |
| Q40242162 | Take care when taking care of fever after aneurysmal subarachnoid hemorrhage |
| Q48395567 | Technology in caring for traumatic brain injury: does what make sense really do? |
| Q38248163 | The International Multi-disciplinary Consensus Conference on Multimodality Monitoring: future directions and emerging technologies |
| Q48127845 | Visualizing secondary brain insults: does the emperor have new clothes? |
| Q35188106 | Windowed multitaper correlation analysis of multimodal brain monitoring parameters |
| Q89249464 | [Specialized neurological neurosurgical intensive care medicine] |
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