AIMC Topic: Fuzzy Logic

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Neural networks and Fuzzy clustering methods for assessing the efficacy of microarray based intrinsic gene signatures in breast cancer classification and the character and relations of identified subtypes.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
In the classification of breast cancer subtypes using microarray data, hierarchical clustering is commonly used. Although this form of clustering shows basic cluster patterns, more needs to be done to investigate the accuracy of clusters as well as t...
Humans Neural Networks, Computer Female Breast Neoplasms Gene Expression Profiling Computational Biology Gene Expression Regulation, Neoplastic Fuzzy Logic Cluster Analysis Oligonucleotide Array Sequence Analysis
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Developing a multimodal biometric authentication system using soft computing methods.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2015
Robust personal authentication is becoming ever more important in computer-based applications. Among a variety of methods, biometric offers several advantages, mainly in embedded system applications. Hard and soft multi-biometric, combined with hard ...
Neural Networks, Computer Algorithms Computers Fuzzy Logic Speech Recognition Software Biometric Identification Dermatoglyphics
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Exploiting expert systems in cardiology: a comparative study.

Advances in experimental medicine and biology Jan 1, 2015
An improved Adaptive Neuro-Fuzzy Inference System (ANFIS) in the field of critical cardiovascular diseases is presented. The system stems from an earlier application based only on a Sugeno-type Fuzzy Expert System (FES) with the addition of an Artifi...
Humans Neural Networks, Computer Reproducibility of Results Sensitivity and Specificity Cardiovascular Diseases Fuzzy Logic Expert Systems Cardiology
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Performance analysis of unsupervised optimal fuzzy clustering algorithm for MRI brain tumor segmentation.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2015
BACKGROUND: Segmentation of brain tumor from Magnetic Resonance Imaging (MRI) becomes very complicated due to the structural complexities of human brain and the presence of intensity inhomogeneities.
Humans Algorithms Sensitivity and Specificity Brain Neoplasms India Magnetic Resonance Imaging Fuzzy Logic Cluster Analysis Image Interpretation, Computer-Assisted Pattern Recognition, Automated Task Performance and Analysis
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