AIMC Topic: Neural Networks, Computer

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A simple pan-specific RNN model for predicting HLA-II binding peptides.

Molecular immunology
The prediction of human leukocyte antigen (HLA) class II binding peptides plays important roles in understanding the mechanism of immune recognition and developing effective epitope-based vaccines. In this work, gated recurrent unit (GRU)-based recur...

Augmented sequence features and subcellular localization for functional characterization of unknown protein sequences.

Medical & biological engineering & computing
Advances in high-throughput techniques lead to evolving a large number of unknown protein sequences (UPS). Functional characterization of UPS is significant for the investigation of disease symptoms and drug repositioning. Protein subcellular localiz...

Robustifying Deep Networks for Medical Image Segmentation.

Journal of digital imaging
The purpose of this study is to investigate the robustness of a commonly used convolutional neural network for image segmentation with respect to nearly unnoticeable adversarial perturbations, and suggest new methods to make these networks more robus...

A rapid segmentation method of cell boundary for developing embryos using machine learning with a personal computer.

Development, growth & differentiation
Cell segmentation is crucial in the study of morphogenesis in developing embryos, but it had been limited in its accuracy until machine learning methods for image segmentation like U-Net. However, these methods take too much time. In this study, we p...

Mechanical Imaging of Soft Tissues With Miniature Climbing Robots.

IEEE transactions on bio-medical engineering
Systematically mapping the mechanical properties of skin and tissue is useful for biomechanics research and disease diagnostics. For example, later stage breast cancer and lymphoma manifest themselves as hard nodes under the skin. Currently, mechanic...

Using Neural Network Force Fields to Ascertain the Quality of Simulations of Liquid Water.

The journal of physical chemistry. B
Accurately simulating the properties of bulk water, despite the apparent simplicity of the molecule, is still a challenge. In order to fully understand and reproduce its complex phase diagram, it is necessary to perform simulations at the level, inc...

Peak learning of mass spectrometry imaging data using artificial neural networks.

Nature communications
Mass spectrometry imaging (MSI) is an emerging technology that holds potential for improving, biomarker discovery, metabolomics research, pharmaceutical applications and clinical diagnosis. Despite many solutions being developed, the large data size ...

Across-Area Synchronization Supports Feature Integration in a Biophysical Network Model of Working Memory.

Frontiers in neural circuits
Working memory function is severely limited. One key limitation that constrains the ability to maintain multiple items in working memory simultaneously is so-called swap errors. These errors occur when an inaccurate response is in fact accurate relat...

EEG-Based Personality Prediction Using Fast Fourier Transform and DeepLSTM Model.

Computational intelligence and neuroscience
In this paper, a deep long short term memory (DeepLSTM) network to classify personality traits using the electroencephalogram (EEG) signals is implemented. For this research, the Myers-Briggs Type Indicator (MBTI) model for predicting personality is ...

An Approach for Thoracic Syndrome Classification with Convolutional Neural Networks.

Computational and mathematical methods in medicine
There have been remarkable changes in our lives and the way we perceive the world with advances in computing technology. Healthcare sector is evolving with the intervention of the latest computer-driven technology and has made a remarkable change in ...