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Related Experiment Videos

Managing the data from respiratory measurements.

J J Osborn, L M Fagan, R J Fallat

    Medical Instrumentation
    |November 1, 1979
    PubMed
    Summary
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    SCRAM: A scoring and ranking system for persistent, bioaccumulative, and toxic substances for the north american great lakes : Part I: Structure of the scoring and ranking system (ESPR No. 1, 2000) DOI: http://dx.doi.org/10.1065/espr 199910.009 Part II: Bioaccumulation potential and persistence (ESPR No.2, 2000) DOI: http://dx.doi.org/10.1065/espr 199910.010 Part III: Acute and subchronic or chronic toxicity (ESPR No. 3, 2000) DOI: http://dx.doi.org/10.1065/espr199910.011 Part IV: Results from representative chemicals, sensitivity analysis, and discriminatory power (ESPR No. 4, 2000).

    Environmental science and pollution research international·2010
    Same author

    SCRAM: A scoring and ranking system for persistent, bioaccumulative, and toxic substances for the North American Great Lakes. Part I: Structure of the scoring and ranking system.

    Environmental science and pollution research international·2009
    Same author

    SCRAM: A scoring and ranking system for persistent, bioaccumulative, and toxic substances for the North American Great Lakes. Part III: Acute and subchronic or chronic toxicity.

    Environmental science and pollution research international·2008
    Same author

    SCRAM: A scoring and ranking system for persistent, bioaccumulative, and toxic substances for the North American Great Lakes.

    Environmental science and pollution research international·2008
    Same author

    SCRAM: A scoring and ranking system for persistent, bioaccumulative, and toxic substances for the North American Great Lakes. Part II: Bioaccumulation potential and persistence.

    Environmental science and pollution research international·2008
    Same author

    SCRAM: A scoring and ranking system for persistent, bioaccumulative, and toxic substances for the North American Great Lakes. Part IV: Results from representative chemicals, sensitivity analysis, and discriminatory power.

    Environmental science and pollution research international·2008
    Same journal

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    Medical instrumentation·1988
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    Medical instrumentation·1988
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    Blood pressure reactivity and bias vary with age in a comparison of traditional and automated methods of measurement.

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    Medical instrumentation·1988
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    Electrically produced artificial ventilation.

    Medical instrumentation·1988
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    Effective clinical decision-making in the ICU requires interpreting complex physiological data. This study introduces mathematical and symbolic processing techniques to enhance quantitative physiological monitoring for better patient care.

    Area of Science:

    • Critical Care Medicine
    • Biomedical Engineering
    • Physiological Monitoring

    Background:

    • Clinical decision-making relies on accurate interpretation of physiological data.
    • No single variable is sufficient for effective patient management in intensive care units (ICUs).
    • Quantitative physiological monitoring offers potential for improved clinical insights.

    Observation:

    • Six case studies highlight the limitations of individual data points in clinical decision-making.
    • Different physiological parameters hold relevance in distinct clinical scenarios.
    • The complexity of ICU data necessitates advanced interpretation methods.

    Findings:

    • Mathematical modeling can quantify lung gas volume in mechanically ventilated patients by analyzing oxygen response transients.

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  • Symbolic processing aids in interpreting the clinical significance of measured data, including artifact recognition.
  • Symbolic processing helps identify patient physiological status and suggest appropriate therapeutic interventions.

    • Implications:

    • These techniques can enhance the effectiveness of clinical decision-making in the ICU.
    • Quantitative data analysis and symbolic interpretation improve the utility of physiological monitoring.
    • Advanced data interpretation methods support personalized and goal-oriented patient therapy.