AIMC Topic: Fuzzy Logic

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Predicting lysine lipoylation sites using bi-profile bayes feature extraction and fuzzy support vector machine algorithm.

Analytical biochemistry
Lipoylation is a highly conserved post-translational modification which has been found to be involved in many biological processes and closely associated with various metabolic diseases. The accurate identification of lipoylation sites is necessary t...

Multimodal Medical Image Fusion Based on Fuzzy Discrimination With Structural Patch Decomposition.

IEEE journal of biomedical and health informatics
Multimodal medical image fusion, emerging as a hot topic, aims to fuse images with complementary multi-source information. In this paper, we propose a novel multimodal medical image fusion method based on structural patch decomposition (SPD) and fuzz...

Fuzzy entropy based on differential evolution for breast gland segmentation.

Australasian physical & engineering sciences in medicine
For the diagnosis and treatment of breast tumors, the automatic detection of glands is a crucial step. The true segmentation of the gland is directly related to effective treatment effect of the patient. Therefore, it is necessary to propose an autom...

A Novel Extension to Fuzzy Connectivity for Body Composition Analysis: Applications in Thigh, Brain, and Whole Body Tissue Segmentation.

IEEE transactions on bio-medical engineering
Magnetic resonance imaging (MRI) is the non-invasive modality of choice for body tissue composition analysis due to its excellent soft-tissue contrast and lack of ionizing radiation. However, quantification of body composition requires an accurate se...

Sequential Integration of Fuzzy Clustering and Expectation Maximization for Transcription Factor Binding Site Identification.

Journal of computational biology : a journal of computational molecular cell biology
The identification of transcription factor binding sites (TFBSs) is a problem for which computational methods offer great hope. Thus far, the expectation maximization (EM) technique has been successfully utilized in finding TFBSs in DNA sequences, bu...

The Fuzziness of the Molecular World and Its Perspectives.

Molecules (Basel, Switzerland)
Scientists want to comprehend and control complex systems. Their success depends on the ability to face also the challenges of the corresponding computational complexity. A promising research line is artificial intelligence (AI). In AI, fuzzy logic p...

FESAEI: a fuzzy rule-based expert system for the assessment of environmental impacts : A fuzzy logic approach to impact assessment.

Environmental monitoring and assessment
Currently, the method mostly used by practitioners of environmental impact assessment (EIA) is the "crisp numbers" method. Nevertheless, this arithmetic method is far away of giving correct values due to its rigidity and the lack of consideration of ...

Uncertainty, imprecision, and many-valued logics in protein bioinformatics.

Mathematical biosciences
Understanding proteins, their structures, functions, mutual interactions, activity in cellular reactions, interactions with drugs, and expression in body cells is a key to efficient medical diagnosis, drug production, and treatment of patients. Machi...

Assessing organizations performance on the basis of GHRM practices using BWM and Fuzzy TOPSIS.

Journal of environmental management
Over the past few years, the need for sustainable environmental management has increased rapidly and green management has emerged as an important tool for the same. The role of Green Human Resource Management (GHRM) practices in environmental managem...

Fuzzy c-means-based architecture reduction of a probabilistic neural network.

Neural networks : the official journal of the International Neural Network Society
The efficiency of the probabilistic neural network (PNN) is very sensitive to the cardinality of a considered input data set. It results from the design of the network's pattern layer. In this layer, the neurons perform an activation on all input rec...