AIMC Topic: Algorithms

Clear Filters Showing 13311 to 13320 of 28713 articles

Optimization and Evaluation of an Intelligent Short-Term Blood Glucose Prediction Model Based on Noninvasive Monitoring and Deep Learning Techniques.

Journal of healthcare engineering
Continuous noninvasive blood glucose monitoring and estimation management by using photoplethysmography (PPG) technology always have a series of problems, such as substantial time variability, inaccuracy, and complex nonlinearity. This paper proposes...

E-Commerce Information System Management Based on Data Mining and Neural Network Algorithms.

Computational intelligence and neuroscience
The rapid development of artificial intelligence technology has led to rapid development in various fields. It has many hidden related customer behavior information and future development trends in the e-commerce information system. The data mining t...

Analysing Hate Speech against Migrants and Women through Tweets Using Ensembled Deep Learning Model.

Computational intelligence and neuroscience
Twitter's popularity has exploded in the previous few years, making it one of the most widely used social media sites. As a result of this development, the strategies described in this study are now more beneficial. Additionally, there has been an in...

Deep learning based object tracking for 3D microstructure reconstruction.

Methods (San Diego, Calif.)
In medical and material science, 3D reconstruction is of great importance for quantitative analysis of microstructures. After the image segmentation process of serial slices, in order to reconstruct each local structure in volume data, it needs to us...

Decoding finger movement patterns from microscopic neural drive information based on deep learning.

Medical engineering & physics
Recent development of surface electromyogram (sEMG) decomposition technique provides a good basis of decoding movements from individual motor unit (MU) activities that directly representing microscopic neural drives. How to interpret the function and...

Evaluation of moyamoya disease in CT angiography using ultra-high-resolution computed tomography: Application of deep learning reconstruction.

European journal of radiology
PURPOSE: The aim of this study was to examine the evaluation of ultra-high-resolution computed tomography angiography (UHR CTA) images in moyamoya disease (MMD) reconstructed with hybrid iterative reconstruction (Hybrid-IR), model-based iterative rec...

Deep learning approach for bubble segmentation from hysteroscopic images.

Medical & biological engineering & computing
Gas embolism is a potentially serious complication of hysteroscopic surgery. It is particularly necessary to monitor bubble parameters in hysteroscopic images by computer vision method for helping develop automatic bubble removal devices. In this wor...

Evaluation of Creep Behavior of Soft Soils by Utilizing Multisensor Data Combined with Machine Learning.

Sensors (Basel, Switzerland)
To identify the unknown values of the parameters of Burger's constitutive law, commonly used for the evaluation of the creep behavior of the soft soils, this paper demonstrates a procedure relying on the data obtained from multiple sensors, where eac...

Electron microscopy of cardiac 3D nanodynamics: form, function, future.

Nature reviews. Cardiology
The 3D nanostructure of the heart, its dynamic deformation during cycles of contraction and relaxation, and the effects of this deformation on cell function remain largely uncharted territory. Over the past decade, the first inroads have been made to...