AI Medical Compendium Topic

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PDGNet: Predicting Disease Genes Using a Deep Neural Network With Multi-View Features.

IEEE/ACM transactions on computational biology and bioinformatics
The knowledge of phenotype-genotype associations is crucial for the understanding of disease mechanisms. Numerous studies have focused on developing efficient and accurate computing approaches to predict disease genes. However, owing to the sparsenes...

Adaptive Learning through Temporal Dynamics of State Representation.

The Journal of neuroscience : the official journal of the Society for Neuroscience
People adjust their learning rate rationally according to local environmental statistics and calibrate such adjustments based on the broader statistical context. To date, no theory has captured the observed range of adaptive learning behaviors or the...

Lidar-Based Navigation of Subterranean Environments Using Bio-Inspired Wide-Field Integration of Nearness.

Sensors (Basel, Switzerland)
Navigating unknown environments is an ongoing challenge in robotics. Processing large amounts of sensor data to maintain localization, maps of the environment, and sensible paths can result in high compute loads and lower maximum vehicle speeds. This...

Cardiac X-ray image-based haptic guidance for robot-assisted coronary intervention: a feasibility study.

International journal of computer assisted radiology and surgery
PURPOSE: Effective and efficient haptic guidance is desirable for tele-operated robotic surgery because it has a potential to enhance surgeon's skills, especially in coronary interventions where surgeon loses both an eye-hand coordination and a direc...

Self-feedback LSTM regression model for real-time particle source apportionment.

Journal of environmental sciences (China)
Atmospheric particulate matter pollution has attracted much wider attention globally. In recent years, the development of atmospheric particle collection techniques has put forwards new demands on the real-time source apportionments techniques. Such ...

Finite-time stabilization of complex-valued neural networks with proportional delays and inertial terms: A non-separation approach.

Neural networks : the official journal of the International Neural Network Society
This article mainly dedicates on the issue of finite-time stabilization of complex-valued neural networks with proportional delays and inertial terms via directly constructing Lyapunov functions without separating the original complex-valued neural n...

Effective TCP Flow Management Based on Hierarchical Feedback Learning in Complex Data Center Network.

Sensors (Basel, Switzerland)
Many studies focusing on improving Transmission Control Protocol (TCP) flow control realize a more effective use of bandwidth in data center networks. They are excellent ways to more effectively use the bandwidth between clients and back-end servers....

Strict-Feedback Backstepping Digital Twin and Machine Learning Solution in AE Signals for Bearing Crack Identification.

Sensors (Basel, Switzerland)
Bearings are nonlinear systems that can be used in several industrial applications. In this study, the combination of a strict-feedback backstepping digital twin and machine learning algorithm was developed for bearing crack type/size diagnosis. Acou...

Adaptive Finite-Time Containment Control of Uncertain Multiple Manipulator Systems.

IEEE transactions on cybernetics
This article is concerned with the containment control of multiple manipulators with uncertain parameters. A novel distributed adaptive backstepping strategy is given in the finite-time control framework. The finite-time command filters (FTCFs) used ...

Guaranteed Cost Finite-Time Control of Uncertain Coupled Neural Networks.

IEEE transactions on cybernetics
This article investigates a robust guaranteed cost finite-time control for coupled neural networks with parametric uncertainties. The parameter uncertainties are assumed to be time-varying norm bounded, which appears on the system state and input mat...