piecewise cubic hermite interpolation method matlab 7.7 r2008b (MathWorks Inc)
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piecewise cubic hermite interpolation method matlab 7.7 r2008b
Piecewise Cubic Hermite Interpolation Method Matlab 7.7 R2008b, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 93/100, based on 21 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/piecewise+cubic+hermite+interpolation+method+matlab+7%2E7+r2008b/MATLAB+Production+Server+Client+Libraries/pm23494545-54-5-13
Average 93 stars, based on 21 article reviews
Piecewise Cubic Hermite Interpolation Method Matlab 7.7 R2008b, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 93/100, based on 21 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/piecewise+cubic+hermite+interpolation+method+matlab+7%2E7+r2008b/MATLAB+Production+Server+Client+Libraries/pm23494545-54-5-13
Average 93 stars, based on 21 article reviews
piecewise cubic hermite interpolation method matlab 7.7 r2008b - by Bioz Stars,
2026-10
93/100 stars
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other:Article Title: Timing of intracranial hypertension following severe traumatic brain injury. Article Snippet: Background We asked whether continuous intracranial pressure (ICP) monitoring data could provide objective measures of the degree and timing of intracranial hypertension (ICH) in the first week of neurotrauma critical care and whether such data could be linked to outcome.. Methods We enrolled adult (>17 years old) patients admitted to our Level I trauma center within 6 h of severe TBI.. ICP data were automatically captured and ICP 5-minute means were grouped into 12-hour time periods from admission (hour 0) to >7 days (hour 180). Article Title: Computational gene mapping to analyze continuous automated physiologic monitoring data in neuro-trauma intensive care Article Snippet: BACKGROUND: We asked whether the advanced machine learning applications used in microarray gene profiling could assess critical thresholds in the massive databases generated by continuous electronic physiologic vital signs (VS) monitoring in the neurotrauma intensive care unit.. METHODS: We used Class Prediction Analysis to predict binary outcomes (life/death, good/bad Extended Glasgow Outcome Score, etc.) based on data accrued within 12, 24, 48, and 72 hours after admission to the neuro-trauma intensive care unit.. Univariate analyses selected ‘‘features,’’ discriminator VS segments or ‘‘genes,’’ in each individual’s data set. |