Method and Label Decision

Keywords Immunohistochemistry Antibody labeling Fluorescence microscopy Fluorescent immunocytochemistry Fluorescent immunohistochemistry Indirect immunocytochemistry Immunostaining 

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Each chapter follows the order of these procedure steps and explains different options. The goal is to give enough information to design a procedure for a particular experimental need. In Chapter 9, Decision Method and Label, an Experimental Design Chart is presented that guides the decisions on reagents for specific experiments. 

The present study aims to develop an uncertain classification process of cerebral palsy using a heuristics-based belief assignment method and belief decision tree method. This helps clinicians to classify two main types of cerebral palsy (diplegia and hemiplegia) with belief label automatically based on gait kinematics, kinetics, and EMG parameters. 

Local interpretation methods encompass a wide variety of approaches that resolve decisions about input data relative to annotated data or known features that cluster. By characterizing the cluster or grouping, it is possible to use various measures to determine whether an arbitary pattern of data can be assigned the same label as the annotated grouping. All approaches are statistical, but they vary in terms of measures, which include statistical distance, variance, probability of occurrence, and pattern similarity. 

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