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Correlation of Data

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Transferability of features for neural networks links to adversarial attacks and defences.

PloS one
The reason for the existence of adversarial samples is still barely understood. Here, we explore the transferability of learned features to Out-of-Distribution (OoD) classes. We do this by assessing neural networks' capability to encode the existing ...

Machine Learning analysis of high-grade serous ovarian cancer proteomic dataset reveals novel candidate biomarkers.

Scientific reports
Ovarian cancer is one of the most common gynecological malignancies, ranking third after cervical and uterine cancer. High-grade serous ovarian cancer (HGSOC) is one of the most aggressive subtype, and the late onset of its symptoms leads in most cas...

Double graph correlation encryption based on hyperchaos.

PloS one
Preventing unauthorized access to sensitive data has always been one of the main concerns in the field of information security. Accordingly, various solutions have been proposed to meet this requirement, among which encryption can be considered as on...

Research on cloud manufacturing service recommendation based on graph neural network.

PloS one
There are an increasing number of manufacturing service resources appeared on the cloud manufacturing (CMfg) service platform recently, which leads to a serious information overloading problem to the enterprises that need these resources. To tackle t...

Three-dimensional CT imaging in extensor tendons using deep learning reconstruction: optimal reconstruction parameters and the influence of dose.

Physical and engineering sciences in medicine
The purpose of this study was to assess the optimal reconstruction parameters and the influence of tube current in extensor tendons three-dimensional computed tomography (3D CT) using deep learning reconstruction, using iterative reconstruction as a ...

A deep learning approach for fully automated measurements of lower extremity alignment in radiographic images.

Scientific reports
During clinical evaluation of patients and planning orthopedic treatments, the periodic assessment of lower limb alignment is critical. Currently, physicians use physical tools and radiographs to directly observe limb alignment. However, this process...

The multi-strategy hybrid forecasting base on SSA-VMD-WST for complex system.

PloS one
In view of the strong randomness and non-stationarity of complex system, this study suggests a hybrid multi-strategy prediction technique based on optimized hybrid denoising and deep learning. Firstly, the Sparrow search algorithm (SSA) is used to op...

Improving structure-based protein-ligand affinity prediction by graph representation learning and ensemble learning.

PloS one
Predicting protein-ligand binding affinity presents a viable solution for accelerating the discovery of new lead compounds. The recent widespread application of machine learning approaches, especially graph neural networks, has brought new advancemen...

Graph-Driven Simultaneous and Proportional Estimation of Wrist Angle and Grasp Force via High-Density EMG.

IEEE journal of biomedical and health informatics
Myoelectric prostheses are generally unable to accurately control the position and force simultaneously, prohibiting natural and intuitive human-machine interaction. This issue is attributed to the limitations of myoelectric interfaces in effectively...

Hallux valgus and pes planus: Correlation analysis using deep learning-assisted radiographic angle measurements.

Foot and ankle surgery : official journal of the European Society of Foot and Ankle Surgeons
BACKGROUND: The relationship between hallux valgus (HV) and pes planus remains unresolved. This study aims to determine the correlation between HV and pes planus using a deep learning (DL) model to measure radiographic angle parameters.