AIMC Topic: Neural Networks, Computer

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Towards stroke prediction using electronic health records.

BMC medical informatics and decision making
BACKGROUND: As of 2014, stroke is the fourth leading cause of death in Japan. Predicting a future diagnosis of stroke would better enable proactive forms of healthcare measures to be taken. We aim to predict a diagnosis of stroke within one year of t...

Application of Chemometric Algorithms in the High-Performance Thin-Layer Chromatography Fingerprint of Traditional Chinese Medicines.

Journal of AOAC International
The use of HPTLC fingerprinting for the analysis of traditional Chinese medicines (TCMs) usually involves several image-processing steps. However, these image-processing steps are time consuming. We describe a new approach that applies artificial n...

Ensemble Neural Networks (ENN): A gradient-free stochastic method.

Neural networks : the official journal of the International Neural Network Society
In this study, an efficient stochastic gradient-free method, the ensemble neural networks (ENN), is developed. In the ENN, the optimization process relies on covariance matrices rather than derivatives. The covariance matrices are calculated by the e...

Neuroevolution as a tool for microarray gene expression pattern identification in cancer research.

Journal of biomedical informatics
Microarrays are still one of the major techniques employed to study cancer biology. However, the identification of expression patterns from microarray datasets is still a significant challenge to overcome. In this work, a new approach using Neuroevol...

Learning Spatial-Spectral-Temporal EEG Features With Recurrent 3D Convolutional Neural Networks for Cross-Task Mental Workload Assessment.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Mental workload assessment is essential for maintaining human health and preventing accidents. Most research on this issue is limited to a single task. However, cross-task assessment is indispensable for extending a pre-trained model to new workload ...

A neural data structure for novelty detection.

Proceedings of the National Academy of Sciences of the United States of America
Novelty detection is a fundamental biological problem that organisms must solve to determine whether a given stimulus departs from those previously experienced. In computer science, this problem is solved efficiently using a data structure called a B...

Face Recognition Using the SR-CNN Model.

Sensors (Basel, Switzerland)
In order to solve the problem of face recognition in complex environments being vulnerable to illumination change, object rotation, occlusion, and so on, which leads to the imprecision of target position, a face recognition algorithm with multi-featu...

Performance of convolutional neural networks for identification of bacteria in 3D microscopy datasets.

PLoS computational biology
Three-dimensional microscopy is increasingly prevalent in biology due to the development of techniques such as multiphoton, spinning disk confocal, and light sheet fluorescence microscopies. These methods enable unprecedented studies of life at the m...

The Design and Implementation of Cardiotocography Signals Classification Algorithm Based on Neural Network.

Computational and mathematical methods in medicine
Mobile medical care is a hot issue in current medical research. Due to the inconvenience of going to hospital for fetal heart monitoring and the limited medical resources, real-time monitoring of fetal health on portable devices has become an urgent ...

Novel neural network application for bacterial colony classification.

Theoretical biology & medical modelling
BACKGROUND: Bacterial colony morphology is the first step of classifying the bacterial species before sending them to subsequent identification process with devices, such as VITEK 2 automated system and mass spectrometry microbial identification syst...