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Adversarial training based lattice LSTM for Chinese clinical named entity recognition.

Journal of biomedical informatics
Clinical named entity recognition (CNER), which intends to automatically detect clinical entities in electronic health record (EHR), is a committed step for further clinical text mining. Recently, more and more deep learning models are used to Chines...

Correlation-Based Ensemble Feature Selection Using Bioinspired Algorithms and Classification Using Backpropagation Neural Network.

Computational and mathematical methods in medicine
A framework for clinical diagnosis which uses bioinspired algorithms for feature selection and gradient descendant backpropagation neural network for classification has been designed and implemented. The clinical data are subjected to data preprocess...

Salience-aware adaptive resonance theory for large-scale sparse data clustering.

Neural networks : the official journal of the International Neural Network Society
Sparse data is known to pose challenges to cluster analysis, as the similarity between data tends to be ill-posed in the high-dimensional Hilbert space. Solutions in the literature typically extend either k-means or spectral clustering with additiona...

Rethinking the performance comparison between SNNS and ANNS.

Neural networks : the official journal of the International Neural Network Society
Artificial neural networks (ANNs), a popular path towards artificial intelligence, have experienced remarkable success via mature models, various benchmarks, open-source datasets, and powerful computing platforms. Spiking neural networks (SNNs), a ca...

Tree-CNN: A hierarchical Deep Convolutional Neural Network for incremental learning.

Neural networks : the official journal of the International Neural Network Society
Over the past decade, Deep Convolutional Neural Networks (DCNNs) have shown remarkable performance in most computer vision tasks. These tasks traditionally use a fixed dataset, and the model, once trained, is deployed as is. Adding new information to...

Human Gait Recognition Based on Frame-by-Frame Gait Energy Images and Convolutional Long Short-Term Memory.

International journal of neural systems
Human gait recognition is one of the most promising biometric technologies, especially for unobtrusive video surveillance and human identification from a distance. Aiming at improving recognition rate, in this paper we study gait recognition using de...

Chinese clinical named entity recognition with radical-level feature and self-attention mechanism.

Journal of biomedical informatics
Named entity recognition is a fundamental and crucial task in medical natural language processing problems. In medical fields, Chinese clinical named entity recognition identifies boundaries and types of medical entities from unstructured text such a...

Adversarial Examples: Opportunities and Challenges.

IEEE transactions on neural networks and learning systems
Deep neural networks (DNNs) have shown huge superiority over humans in image recognition, speech processing, autonomous vehicles, and medical diagnosis. However, recent studies indicate that DNNs are vulnerable to adversarial examples (AEs), which ar...

Exploration of Chinese Sign Language Recognition Using Wearable Sensors Based on Deep Belief Net.

IEEE journal of biomedical and health informatics
In this paper, deep belief net (DBN) was applied into the field of wearable-sensor based Chinese sign language (CSL) recognition. Eight subjects were involved in the study, and all of the subjects finished a five-day experiment performing CSL on a ta...

A superpixel-driven deep learning approach for the analysis of dermatological wounds.

Computer methods and programs in biomedicine
BACKGROUND: The image-based identification of distinct tissues within dermatological wounds enhances patients' care since it requires no intrusive evaluations. This manuscript presents an approach, we named QTDU, that combines deep learning models wi...