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Median Error (median + error)

Distribution by Scientific Domains

Medical Sciences	75%

Selected Abstracts

Estimating missing daily temperature extremes using an optimized regression approach

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 11 2001
Robert J. Allen
Abstract A variation of a least squares regression approach to estimate missing daily maximum and minimum temperatures is developed and evaluated, specifically for temperature extremes. The method focuses on obtaining accurate estimates of annual exceedence counts (e.g. the number of days greater than or equal to the 90th percentile of daily maximum temperatures), as well as counts of consecutive exceedences, while limiting the estimation error associated with each individual value. The performance of this method is compared with that of two existing methods developed for the entire temperature distribution. In these existing methods, temperature estimates are based on data from neighbouring stations using either regression or temperature departure-based approaches. Evaluation of our approach using cold minimum and warm maximum temperatures shows that the median percentage of correctly identified exceedence counts is 97% and the median percentage of correctly identified consecutive exceedence counts is 98%. The other existing methods tend to underestimate both single and consecutive exceedence counts. Using these procedures, the estimated exceedence counts are generally less than 80% of those that actually occurred. Despite the fact that our method is tuned to estimate exceedence counts, the estimation accuracy of individual daily maximum or minimum temperatures is similar to that of the other estimation procedures. The median absolute error (MAE) using all temperatures greater than or equal to the 90th percentile (T90),1.1°C for ten climatically diverse stations is 1.28°C for our method, while the other methods give MAEs of 1.27 and 1.17°C. In terms of median error, however, the tendency for underprediction by the existing methods is pronounced with ,0.77 and ,0.61°C biases. Our optimized method is relatively unbiased as the resulting mean error is ,0.12°C. Copyright © 2001 Royal Meteorological Society [source]

Prediction of human pharmacokinetics , improving microsome-based predictions of hepatic metabolic clearance

JOURNAL OF PHARMACY AND PHARMACOLOGY: AN INTERNATI ONAL JOURNAL OF PHARMACEUTICAL SCIENCE, Issue 10 2007
Urban Fagerholm
Physiologically based methods generally perform poorly in predicting in-vivo hepatic CL (CLH) from intrinsic clearance (CLint) in microsomes in-vitro and unbound fraction in blood (fu,bl). Various strategies to improve the predictability have been developed, and inclusion of an empirical scaling factor (SF) seems to give the best results. This investigation was undertaken to evaluate this methodology and to find ways to improve it further. The work was based on a diverse data set taken from Ito and Houston (2005). Another objective was to evaluate whether rationalization of CLH predictions can be made by replacing blood/plasma-concentration ratio (Cbl/Cpl) measurements with SFs. There were apparently no or weak correlations between prediction errors and lipophilicity, permeability (compounds with low permeability missing in the data set) and main metabolizing CYP450s. The use of CLint class (high/low) and drug class (acid/base/neutral) SFs (the CD-SF method) gives improved and reasonable predictions: 1.3-fold median error (an accurate prediction has a 1-fold error), 76% within 2-fold-error, and a median absolute rank ordering error of 2 for CLH (n = 29). This approach is better than the method with a single SF. Mean (P < 0.05) and median errors, fraction within certain error ranges, higher percentage with most accurate predictions, and ranking were all better, and 76% of predictions were more accurate with this new method. Results are particularly good for bases, which generally have higher CLH and the potential to be incorrectly selected/rejected as candidate drugs. Reasonable predictions of fu,bl can be made from plasma fu (fu,pl) and empirical blood cell binding SFs (B-SFs; 1 for low fu,pl acids; 0.62 for other substances). Mean and median fu,bl prediction errors are negligible. The use of the CD-SF method with predicted fu,bl (the BCD-SF method) also gives improved and reasonable results (1.4-fold median error; 66% within 2-fold-error; median absolute rank ordering error = 1). This new empirical approach seems sufficiently good for use during the early screening; it gives reasonable estimates of CLH and good ranking, which allows replacement of Cbl/Cpl measurements by a simple equation. [source]

Towards automatic computer-aided knee surgery by innovative methods for processing the femur surface model

THE INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY, Issue 3 2010
Pietro Cerveri
Abstract Background The femoral shaft (FDA) and transepicondylar (TA), anterior,posterior (WL) and posterior condylar (PCL) axes are fundamental quantities in planning knee arthroplasty surgery. As an alternative to the TA, we introduce the anatomical flexion axis (AFA). Obtaining such axes from image data without any manual supervision remains a practical objective. We propose a novel method that automatically computes the axes of the distal femur by processing the femur mesh surface. Methods Surface data were processed by exploiting specific geometric, anatomical and functional properties. Robust ellipse fitting of the two-dimensional (2D) condylar profiles was utilized to determine the AFA alternative to the TA. The repeatability of the method was tested upon 20 femur surfaces reconstructed from CT scans taken on cadavers. Results At the highest surface resolutions, the relative median error in the direction of the FDA, AFA, PCL, WL and TA was < 0.50°, 1.20°, 1.0°, 1.30° and 1.50°, respectively. As expected, at the lowest surface resolution, the repeatability decreased to 1.20°, 2.70°, 3.30°, 3.0° and 4.70°, respectively. The computed directions of the FDA, PCL, WL and TA were in agreement (0.60°, 1.55°, 1.90°, 2.40°) with the corresponding reference parameters manually identified in the original CT images by medical experts and with the literature. Conclusions The proposed method proved that: (a) the AFA can be robustly computed by a geometrical analysis of the posterior profiles of the two condyles and can be considered a useful alternative to the TA; (b) higher surface resolutions leads to higher repeatability of all computed quantities; (c) the TA is less repeatable than the other axes. Copyright © 2010 John Wiley & Sons, Ltd. [source]