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What Is a Digital Twin? Experimental Design for a Data-Centric Machine Learning Perspective in Health.

International journal of molecular sciences
The idea of a digital twin has recently gained widespread attention. While, so far, it has been used predominantly for problems in engineering and manufacturing, it is believed that a digital twin also holds great promise for applications in medicine...

Semantic Annotation of Experimental Methods in Analytical Chemistry.

Analytical chemistry
A major obstacle for reusing and integrating existing data is finding the data that is most relevant in a given context. The primary metadata resource is the scientific literature describing the experiments that produced the data. To stimulate the de...

Comparison of Perioperative Outcomes Between Retroperitoneal Single-Port and Multiport Robot-Assisted Partial Nephrectomies.

Journal of endourology
To report early institutional experience with the single-port robotic platform and compare perioperative outcomes between single-port robot-assisted partial nephrectomies (SP-RAPN) and multiport robot-assisted partial nephrectomies (MP-RAPN) when ut...

Multi-objective data enhancement for deep learning-based ultrasound analysis.

BMC bioinformatics
Recently, Deep Learning based automatic generation of treatment recommendation has been attracting much attention. However, medical datasets are usually small, which may lead to over-fitting and inferior performances of deep learning models. In this ...

Deep mendelian randomization: Investigating the causal knowledge of genomic deep learning models.

PLoS computational biology
Multi-task deep learning (DL) models can accurately predict diverse genomic marks from sequence, but whether these models learn the causal relationships between genomic marks is unknown. Here, we describe Deep Mendelian Randomization (DeepMR), a meth...

Fast Underwater Optical Beacon Finding and High Accuracy Visual Ranging Method Based on Deep Learning.

Sensors (Basel, Switzerland)
Visual recognition and localization of underwater optical beacons is an important step in autonomous underwater vehicle (AUV) docking. The main issues that restrict the use of underwater monocular vision range are the attenuation of light in water, t...

Adaptive Neural Safe Tracking Control Design for a Class of Uncertain Nonlinear Systems With Output Constraints and Disturbances.

IEEE transactions on cybernetics
In this article, an adaptive neural safe tracking control scheme is studied for a class of uncertain nonlinear systems with output constraints and unknown external disturbances. To allow the output to stay in the desired output constraints, a boundar...

Improving Lateral Resolution in 3-D Imaging With Micro-beamforming Through Adaptive Beamforming by Deep Learning.

Ultrasound in medicine & biology
There is an increased desire for miniature ultrasound probes with small apertures to provide volumetric images at high frame rates for in-body applications. Satisfying these increased requirements makes simultaneous achievement of a good lateral reso...

A Particleboard Surface Defect Detection Method Research Based on the Deep Learning Algorithm.

Sensors (Basel, Switzerland)
Particleboard surface defects have a significant impact on product quality. A surface defect detection method is essential to enhancing the quality of particleboard because the conventional defect detection method has low accuracy and efficiency. Thi...

Graph-Based Bayesian Optimization for Large-Scale Objective-Based Experimental Design.

IEEE transactions on neural networks and learning systems
Design is an inseparable part of most scientific and engineering tasks, including real and simulation-based experimental design processes and parameter/hyperparameter tuning/optimization. Several model-based experimental design techniques have been d...