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Interval Neutrosophic Sets and Logic: Theory and Applications in Computing
TLDR
This work defines the set-theoretic operators on an instance of a neutrosophic set, and calls it an Interval Neutrosophics Set (INS), and introduces a new logic system based on interval neutrosophile sets and proposed data model based on the extension of fuzzy data model and paraconsistent data model.
SVMs Modeling for Highly Imbalanced Classification
TLDR
Of the four SVM variations considered in this paper, the novel granular SVMs-repetitive undersampling algorithm (GSVM-RU) is the best in terms of both effectiveness and efficiency.
A Network Integration Approach for Drug-Target Interaction Prediction and Computational Drug Repositioning from Heterogeneous Information
TLDR
The novel interactions between three drugs and the cyclooxygenase (COX) protein family are experimentally validated, and the new potential applications of these identified COX inhibitors are demonstrated in preventing inflammatory diseases.
A network integration approach for drug-target interaction prediction and computational drug repositioning from heterogeneous information
TLDR
DTINet is introduced, whose performance is enhanced in the face of noisy, incomplete and high-dimensional biological data by learning low-dimensional vector representations, which accurately explains the topological properties of individual nodes in the heterogeneous network.
Support vector machines and Word2vec for text classification with semantic features
TLDR
This work demonstrates the effectiveness ofword2vec by showing that tf-idf and word2vec combined can outperform tf-IDf because word2 Vec provides complementary features (e.g. semantics that TF-idF can't capture) to tf- idf.
Brain MRI analysis for Alzheimer’s disease diagnosis using an ensemble system of deep convolutional neural networks
TLDR
A deep convolutional neural network can identify different stages of Alzheimer’s disease and obtains superior performance for early-stage diagnosis and outperformed comparative baselines on the Open Access Series of Imaging Studies dataset.
Development of Two-Stage SVM-RFE Gene Selection Strategy for Microarray Expression Data Analysis
TLDR
It is demonstrated that the two-stage SVM-RFE is significantly more accurate and more reliable than the SVM - Recursive Feature Elimination and three correlation-based methods based on the analysis of three publicly available microarray expression datasets.
Compensatory neurofuzzy systems with fast learning algorithms
TLDR
A new adaptive fuzzy reasoning method using compensatory fuzzy operators is proposed to make a fuzzy logic system more adaptive and more effective and is proved to be a universal approximator.
A Novel Deep Learning Based Multi-class Classification Method for Alzheimer's Disease Detection Using Brain MRI Data
TLDR
A novel deep learning model for multi-Class Alzheimer’s Disease detection and classification using Brain MRI Data is designed and demonstrated and the performance on the Open Access Series of Imaging Studies (OASIS) database is demonstrated.
Visual Sentiment Analysis for Social Images Using Transfer Learning Approach
TLDR
A novel visual sentiment analysis framework using transfer learning approach to predict sentiment is proposed and hyper-parameters learned from a very deep convolutional neural network are used to initialize the network model to prevent overfitting.
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