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A set of 7 key signaling pathways and 7 hub genes were identified with high potential associated with the disease risk. Biomedical text mining was the subject of the article from A. In particular, the author proposed an efficient multiple classifier approach to text categorization based on swarm-optimized latent Dirichlet allocation and diversity-based ensemble pruning. The proposed technique was applied to five biomedical text benchmarks. Results showed that the proposed technique outperformed other state-of-the-art classification algorithms, as well as various ensemble learning and ensemble pruning methods.
In article from Y.
Li et al. In particular, after having applied feature selection and imbalanced processing techniques, the authors applied Support Vector Machine, Decision Trees, Adaboost, and Bagging to the resulting data.
Results showed that Adaboost was the most successful technique for classifying this kind of data.
Following these results, an analysis of the most relevant features was also conducted. In their work, B. Yang and coworkers address the problem of studying the neural activity under cognitive reappraisal on simultaneous EEG electroencephalography -fMRI functional magnetic resonance imaging data.
Results show that the proposed EEG-fMRI fusion approach provides an effective way to study the neural activities of cognitive reappraisal with high spatiotemporal resolution. A novel tool for the optimization of the structure of gene networks is proposed in the article from F.
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FAQ Policy. About this book Taking inspiration from the brain structure neurons , linguistic rather than precise way of description by humans not so cold, very warm , genetics and the behaviour of birds and ants in the nature, new techniques for the solution of various problems have been developed over the past three decades or so.
Malik, Professor Emeritus, University of Calgary. Show all.
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