Search Results - "Khan, Jafar A"

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  1. 1

    Robust Linear Model Selection Based on Least Angle Regression by Khan, Jafar A, Van Aelst, Stefan, Zamar, Ruben H

    “…In this article we consider the problem of building a linear prediction model when the number of candidate predictors is large and the data possibly contain…”
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    Journal Article
  2. 2

    A novel method of light projection and modular jigs to improve accuracy in bone sarcoma resection by He, Guangyu, Dai, Amos Z., Mustahsan, Vamiq M., Shah, Aadit T., Li, Liming, Khan, Jafar A., Bielski, Michael R., Komatsu, David E., Kao, Imin, Khan, Fazel A.

    Published in Journal of orthopaedic research (01-11-2022)
    “…We developed a novel method using a combined light‐registration/light‐projection system along with an off‐the‐shelf, instant‐assembly modular jig construct…”
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    Journal Article
  3. 3

    Fast robust estimation of prediction error based on resampling by Khan, Jafar A., Van Aelst, Stefan, Zamar, Ruben H.

    Published in Computational statistics & data analysis (01-12-2010)
    “…Robust estimators of the prediction error of a linear model are proposed. The estimators are based on the resampling techniques cross-validation and bootstrap…”
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    Journal Article
  4. 4

    A novel intraoperative method to project osteotomy lines for accurate resection of primary bone sarcomas by He, Guangyu, Dai, Amos Z., Mustahsan, Vamiq M., Shah, Aadit T., Li, Liming, Khan, Jafar A., Bielski, Michael R., Komatsu, David E., Kao, Imin, Khan, Fazel A.

    Published in Journal of orthopaedics (01-07-2022)
    “…Accurate reproduction of a preoperative plan is critical in wide resection of bone sarcomas. Recent advances in computer navigation and 3D-custom jigs have…”
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    Journal Article
  5. 5

    Building a robust linear model with forward selection and stepwise procedures by Khan, Jafar A., Van Aelst, Stefan, Zamar, Ruben H.

    Published in Computational statistics & data analysis (15-09-2007)
    “…Classical step-by-step algorithms, such as forward selection (FS) and stepwise (SW) methods, are computationally suitable, but yield poor results when the data…”
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