AIMC Topic: Algorithms

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Incorporation of residual attention modules into two neural networks for low-dose CT denoising.

Medical physics
PURPOSE: The low-dose computed tomography (CT) imaging can reduce the damage caused by x-ray radiation to the human body. However, low-dose CT images have a different degree of artifacts than conventional CT images, and their resolution is lower than...

Protein design and variant prediction using autoregressive generative models.

Nature communications
The ability to design functional sequences and predict effects of variation is central to protein engineering and biotherapeutics. State-of-art computational methods rely on models that leverage evolutionary information but are inadequate for importa...

Collective and synchronous dynamics of photonic spiking neurons.

Nature communications
Nonlinear dynamics of spiking neural networks have recently attracted much interest as an approach to understand possible information processing in the brain and apply it to artificial intelligence. Since information can be processed by collective sp...

Heterogeneous bi-directional recurrent neural network combining fusion health indicator for predictive analytics of rotating machinery.

ISA transactions
Data-driven intelligent methods arise the increasing demand for predictive analytics to evaluate the operational reliability and natural degradation of rotating machinery. Nevertheless, accurate and timely predictive analytics is still regarded as an...

Deep learning-based denoising algorithm in comparison to iterative reconstruction and filtered back projection: a 12-reader phantom study.

European radiology
OBJECTIVES: (1) To compare low-contrast detectability of a deep learning-based denoising algorithm (DLA) with ADMIRE and FBP, and (2) to compare image quality parameters of DLA with those of reconstruction methods from two different CT vendors (ADMIR...

Clinical Application of Machine Learning-Based Artificial Intelligence in the Diagnosis, Prediction, and Classification of Cardiovascular Diseases.

Circulation journal : official journal of the Japanese Circulation Society
With the rapid development of artificial intelligence (AI) and machine learning (ML), as well as the arrival of the big data era, technological innovations have occurred in the field of cardiovascular medicine. First, the diagnosis of cardiovascular ...

Automatic detection of procedural knowledge in robotic-assisted surgical texts.

International journal of computer assisted radiology and surgery
PURPOSE: The automatic extraction of knowledge about intervention execution from surgical manuals would be of the utmost importance to develop expert surgical systems and assistants. In this work we assess the feasibility of automatically identifying...

Predicting the performance of anaerobic digestion using machine learning algorithms and genomic data.

Water research
Modeling of anaerobic digestion (AD) is crucial to better understand the process dynamics and to improve the digester performance. This is an essential yet difficult task due to the complex and unknown interactions within the system. The application ...

Research on nondestructive identification of grape varieties based on EEMD-DWT and hyperspectral image.

Journal of food science
Grape varieties are directly related to the quality and sales price of table grapes and consumed products (raisin, wine, grape juice, etc.). To satisfy the identification requirements of rapid, accurate, and nondestructive detection, an improved deno...

Development of the Ultralight Hybrid Pneumatic Artificial Muscle: Modelling and optimization.

PloS one
Pneumatic artificial muscles (PAMs) are one of the key technologies in soft robotics, and they enable actuation in mobile robots, in wearable devices and exoskeletons for assistive and rehabilitative purposes. While they recently showed relevant impr...