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One model per entity: using hundreds of machine learning models to recognize and normalize biomedical names in text
We explored a new approach to named entity recognition based on hundreds of machine learning models, each trained to distinguish a single entity, and showed its application to gene name identification (GNI).
Bayesian Conditional Gaussian Network Classifiers with Applications to Mass Spectra Classification
Classifiers based on probabilistic graphical models are very effective.
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