AIMC Topic: Neural Networks, Computer

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Inter-database validation of a deep learning approach for automatic sleep scoring.

PloS one
STUDY OBJECTIVES: Development of inter-database generalizable sleep staging algorithms represents a challenge due to increased data variability across different datasets. Sharing data between different centers is also a problem due to potential restr...

Deep Convolutional Clustering-Based Time Series Anomaly Detection.

Sensors (Basel, Switzerland)
This paper presents a novel approach for anomaly detection in industrial processes. The system solely relies on unlabeled data and employs a 1D-convolutional neural network-based deep autoencoder architecture. As a core novelty, we split the autoenco...

Deep learning with convolutional neural network for estimation of the characterisation of coronary plaques: Validation using IB-IVUS.

Radiography (London, England : 1995)
INTRODUCTION: Deep learning approaches have shown high diagnostic performance in image classifications, such as differentiation of malignant tumors and calcified coronary plaque. However, it is unknown whether deep learning is useful for characterizi...

Non-differentiable saddle points and sub-optimal local minima exist for deep ReLU networks.

Neural networks : the official journal of the International Neural Network Society
Whether sub-optimal local minima and saddle points exist in the highly non-convex loss landscape of deep neural networks has a great impact on the performance of optimization algorithms. Theoretically, we study in this paper the existence of non-diff...

Deep learning approach to assess damage mechanics of bone tissue.

Journal of the mechanical behavior of biomedical materials
Machine learning methods have the potential to transform imaging techniques and analysis for healthcare applications with automation, making diagnostics and treatment more accurate and efficient, as well as to provide mechanistic insights into tissue...

TSU-net: Two-stage multi-scale cascade and multi-field fusion U-net for right ventricular segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Accurate segmentation of the right ventricle from cardiac magnetic resonance images (MRI) is a critical step in cardiac function analysis and disease diagnosis. It is still an open problem due to some difficulties, such as a large variety of object s...

Wide & Deep neural network model for patch aggregation in CNN-based prostate cancer detection systems.

Computers in biology and medicine
Prostate cancer (PCa) is one of the most commonly diagnosed cancer and one of the leading causes of death among men, with almost 1.41 million new cases and around 375,000 deaths in 2020. Artificial Intelligence algorithms have had a huge impact on me...

HELLO: improved neural network architectures and methodologies for small variant calling.

BMC bioinformatics
BACKGROUND: Modern Next Generation- and Third Generation- Sequencing methods such as Illumina and PacBio Circular Consensus Sequencing platforms provide accurate sequencing data. Parallel developments in Deep Learning have enabled the application of ...

Artificial intelligence to improve efficiency of administration of gross motor function assessment in children with cerebral palsy.

Developmental medicine and child neurology
AIM: To create a reduced version of the 66-item Gross Motor Function Measure (rGMFM-66) using innovative artificial intelligence methods to improve efficiency of administration of the GMFM-66.

Schematic memory persistence and transience for efficient and robust continual learning.

Neural networks : the official journal of the International Neural Network Society
Continual learning is considered a promising step toward next-generation Artificial Intelligence (AI), where deep neural networks (DNNs) make decisions by continuously learning a sequence of different tasks akin to human learning processes. It is sti...