Search Results - "Land, Walker H"

Statistical learning techniques applied to epidemiology: a simulated case-control comparison study with logistic regression by Heine, John J, Land, Walker H, Egan, Kathleen M

“…When investigating covariate interactions and group associations with standard regression analyses, the relationship between the response variable and exposure…”
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Targeting Chemical and Biological Warfare Agents at the Molecular Level by Sadik, Omowunmi A., Land Jr, Walker H., Wang, Joseph

“…After the September 11 tragedies of 2001, scientists and law‐enforcement agencies have shown increasing concern that terrorist organizations and their “rogue”…”
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Improving CT prediction of treatment response in patients with metastatic colorectal carcinoma using statistical learning theory by Land, Walker H, Margolis, Dan, Gottlieb, Ronald, Krupinski, Elizabeth A, Yang, Jack Y

“…Significant interest exists in establishing radiologic imaging as a valid biomarker for assessing the response of cancer to a variety of treatments. To address…”
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Statistical learning methods as a preprocessing step for survival analysis: evaluation of concept using lung cancer data by Behera, Madhusmita, Fowler, Erin E, Owonikoko, Taofeek K, Land, Walker H, Mayfield, William, Chen, Zhengjia, Khuri, Fadlo R, Ramalingam, Suresh S, Heine, John J

“…Statistical learning (SL) techniques can address non-linear relationships and small datasets but do not provide an output that has an epidemiologic…”
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Perturbation and candidate analysis to combat overfitting of gene expression microarray data by Mathur, Ravi, Schaffer, J David, Land, Jr, Walker H, Heine, John J, Hernandez, Jonathan M, Yeatman, Timothy

“…Analysis of gene expression microarray datasets presents the high risk of over-fitting (spurious patterns) because of their feature-rich but case-poor nature…”
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Kernelized partial least squares for feature reduction and classification of gene microarray data by Land, Walker H, Qiao, Xingye, Margolis, Daniel E, Ford, William S, Paquette, Christopher T, Perez-Rogers, Joseph F, Borgia, Jeffrey A, Yang, Jack Y, Deng, Youping

“…The primary objectives of this paper are: 1.) to apply Statistical Learning Theory (SLT), specifically Partial Least Squares (PLS) and Kernelized PLS (K-PLS),…”
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Multiclass primal support vector machines for breast density classification by Land, Jr, Walker H, Verheggen, Elizabeth A

“…Parenchymal patterns defining the density of breast tissue are detected by advanced correlation pattern recognition in an integrated Computer-Aided Detection…”
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Improving CT prediction of treatment response in patients with metastatic colorectal carcinoma using statistical learning by Land, Jr, Walker H, Margolis, Dan, Gottlieb, Ronald, Yang, Jack Y, Krupinski, Elizabeth A

“…To establish radiologic imaging as a valid biomarker for assessing the response of cancer to different treatments. We study patients with metastatic colorectal…”
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Detection and Classification of Organophosphate Nerve Agent Simulants Using Support Vector Machines with Multiarray Sensors by Sadik, Omowunmi, Land, Walker H, Wanekaya, Adam K, Uematsu, Michiko, Embrechts, Mark J, Wong, Lut, Leibensperger, Dale, Volykin, Alex

“…The need for rapid and accurate detection systems is expanding and the utilization of cross-reactive sensor arrays to detect chemical warfare agents in…”
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Kernelized partial least squares for feature reduction and classification of gene microarray data by Land, Walker H, Qiao, Xingye, Margolis, Daniel E, Ford, William S, Paquette, Christopher T, Perez-Rogers, Joseph F, Borgia, Jeffrey A, Yang, Jack Y, Deng, Youping

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Applying support vector machines to breast cancer diagnosis using screen film mammogram data by Land, W.H., Wong, L., McKee, D., Embrechts, M., Salih, R., Anderson, F.

“…This paper explores the use of different support vector machines (SVM) kernels, and combinations of kernels, to ascertain the diagnostic accuracy of a screen…”
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An End-to-End Process for Cancer Identification from Images of Lung Tissue by Land, W.H., Mckee, D., Zhukov, T., Dansheng Song

“…This research describes a non-interactive process that applies several forms of computational intelligence to the task of classifying biopsy lung tissue…”
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Advancements in Automated Diagnostic Mammography by Land, W.H., Mizaku, A., Raway, T., Heine, J., Berman, C., Kovalchuk, N.

“…This paper reports the results of an initial false positive (FP) investigation using a full set of mammogram risk factors, using a combination of logistic…”
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Performance tradeoff between evolutionary computation (EC)/adaptive boosting (AB) hybrid and support vector machine breast cancer classification paradigms by Land, W.H., Bryden, M., Lo, J.Y., McKee, D.W., Anderson, F.R.

“…This paper describes a breast cancer classification performance trade-off analysis using two computational intelligence paradigms. The first, an evolutionary…”
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