Data Mining, Systems Analysis, and Optimization in Biomedicine
Onur Seref, O. Erhun Kundakcioglu, Panos M. Pardalos
American Inst. of Physics, Nov 26, 2007 - Medical - 318 pages
This book is a collection of a sample of the latest research methods in data mining across diverse fields of biomedicine, neuroscience, engineering, and computer science. The problems and methods discussed in this book will be of great interest to new and established theoreticians and practitioners in these fields and provide them with new directions for research. The book will be required reading for biomedical and industrial engineers, computer scientists, and medical doctors.
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Employing Optimization and Sensitivity Analyses Tools to Generate
Automated MR Image Processing and Analysis of Malignant Brain
Nonparametric Smoothing and Its Applications in Biomedical
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agarose algorithm application approach Bayesian networks biclustering biomedical Biomedicine brain tumors C-GRASP cancer types cartilage cell CGH data classification models clinical clusters computed constraints construct correlation CpG islands data mining database dataset defined denote developed discriminant disease drug dynamics EEG data EEG recordings effect electrodes epilepsy equation estimate experimental eye movements genes genomic genomic intervals global Granger causality Harmony Search Iasemidis linear Lmax Lyapunov exponent Magnetic Resonance Mammadov Mangasarian markers mathematical models matrix measure metaheuristic methods minimizing misclassification Monkey Search nonlinear normal objective function obtained optimization problem output oxygen P. M. Pardalos patients patterns phase phase-rotation prediction probes programming protein pulse receptors region Research saccade Sackellares samples segmentation seizure detection selected sequence signal smoothing solution statistical support vector machines surrogate targets techniques TFBMs tissue vagus nerve stimulation values variables VNS stimulation voxel