Neural Networks
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Discover non-linear relationships. Can assess multi-level interactions
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“Black Box” to clinicians; hard to implement into a DSS*
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Random Forests
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Finds most probable solution set; robust against scaling influences
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Not always best in terms of prediction; hard to implement into a DSS
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Cluster Analysis
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Finds groups of very similar patients; exploratory analysis
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Unsupervised technique
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Principal Components Analysis
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Uncovers the variables contributing the most to outcome variation
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Not amenable to binary outcomes; assumes additive relationship
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Support Vector Machines
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Robust against statistical assumptions
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Difficult to implement into a DSS
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