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Found 8 papers, 1 papers with code
Medical Image Generation using Generative Adversarial Networks
Generative adversarial networks (GANs) are unsupervised Deep Learning approach in the computer vision community which has gained significant attention from the last few years in identifying the internal structure of multimodal medical imaging data.
A Tour of Unsupervised Deep Learning for Medical Image Analysis
Interpretation of medical images for diagnosis and treatment of complex disease from high-dimensional and heterogeneous data remains a key challenge in transforming healthcare.
Optimizing Deep Neural Network Architecture: A Tabu Search Based Approach
The performance of Feedforward neural network (FNN) fully de-pends upon the selection of architecture and training algorithm.
Analysis of Microarray Data using Artificial Intelligence Based Techniques
Microarray is one of the essential technologies used by the biologist to measure genome-wide expression levels of genes in a particular organism under some particular conditions or stimuli.
Formal Concept Analysis for Knowledge Discovery from Biological Data
Due to rapid advancement in high-throughput techniques, such as microarrays and next generation sequencing technologies, biological data are increasing exponentially.
Recurrent Neural Network Based Hybrid Model of Gene Regulatory Network
The RNN is a complex neural network that gives a better settlement between the biological closeness and mathematical flexibility to model GRN.
Ant Colony Optimization for Inferring Key Gene Interactions
Inferring gene interaction network from gene expression data is an important task in systems biology research.
A Comprehensive Evaluation of Machine Learning Techniques for Cancer Class Prediction Based on Microarray Data
Attribute reduction or gene filtering is absolutely required in order to make the data more meaningful as most of the genes do not participate in tumor development and are irrelevant for cancer prediction.
