AIMC Topic: Neural Networks, Computer

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Noise Reduction Learning Based on XLNet-CRF for Biomedical Named Entity Recognition.

IEEE/ACM transactions on computational biology and bioinformatics
In recent years, Biomedical Named Entity Recognition (BioNER) systems have mainly been based on deep neural networks, which are used to extract information from the rapidly expanding biomedical literature. Long-distance context autoencoding language ...

ctPISP: Protein-Protein Interaction Sites Prediction Using Convolution and Transformer With Data Augmentation.

IEEE/ACM transactions on computational biology and bioinformatics
Protein-protein interactions are the basis of many cellular biological processes, such as cellular organization, signal transduction, and immune response. Identifying protein-protein interaction sites is essential for understanding the mechanisms of ...

DeepSide: A Deep Learning Approach for Drug Side Effect Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
Drug failures due to unforeseen adverse effects at clinical trials pose health risks for the participants and lead to substantial financial losses. Side effect prediction algorithms have the potential to guide the drug design process. LINCS L1000 dat...

Convolution Neural Networks Using Deep Matrix Factorization for Predicting Circrna-Disease Association.

IEEE/ACM transactions on computational biology and bioinformatics
CircRNAs have a stable structure, which gives them a higher tolerance to nucleases. Therefore, the properties of circular RNAs are beneficial in disease diagnosis. However, there are few known associations between circRNAs and disease. Biological exp...

Multiclass datasets expand neural network utility: an example on ankle radiographs.

International journal of computer assisted radiology and surgery
PURPOSE: Artificial intelligence in computer vision has been increasingly adapted in clinical application since the implementation of neural networks, potentially providing incremental information beyond the mere detection of pathology. As its algori...

Automated localization of the medial clavicular epiphyseal cartilages using an object detection network: a step towards deep learning-based forensic age assessment.

International journal of legal medicine
BACKGROUND: Deep learning is a promising technique to improve radiological age assessment. However, expensive manual annotation by experts poses a bottleneck for creating large datasets to appropriately train deep neural networks. We propose an objec...

CrimeNet: Neural Structured Learning using Vision Transformer for violence detection.

Neural networks : the official journal of the International Neural Network Society
The state of the art in violence detection in videos has improved in recent years thanks to deep learning models, but it is still below 90% of average precision in the most complex datasets, which may pose a problem of frequent false alarms in video ...

Simultaneous approximation of a smooth function and its derivatives by deep neural networks with piecewise-polynomial activations.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the approximation properties of deep neural networks with piecewise-polynomial activation functions. We derive the required depth, width, and sparsity of a deep neural network to approximate any Hölder smooth function up to a ...

Histopathological diagnosis of colon cancer using micro-FTIR hyperspectral imaging and deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Current studies based on digital biopsy images have achieved satisfactory results in detecting colon cancer despite their limited visual spectral range. Such methods may be less accurate when applied to samples taken from th...

Fractional derivative based weighted skip connections for satellite image road segmentation.

Neural networks : the official journal of the International Neural Network Society
Segmentation of a road portion from a satellite image is challenging due to its complex background, occlusion, shadows, clouds, and other optical artifacts. One must combine both local and global cues for an accurate and continuous/connected road net...