AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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Pumping machine fault diagnosis based on fused RDC-RBF.

PloS one
At present, the fault diagnosis of pumping units in major oil fields in China is time-consuming and inefficient, and there is no universal problem for high requirements of hardware resources. In this study, a fault fusion diagnosis method of pumping ...

Analysis on the inherent noise tolerance of feedforward network and one noise-resilient structure.

Neural networks : the official journal of the International Neural Network Society
In the past few decades, feedforward neural networks have gained much attraction in their hardware implementations. However, when we realize a neural network in analog circuits, the circuit-based model is sensitive to hardware nonidealities. The noni...

Using Feature Engineering and Principal Component Analysis for Monitoring Spindle Speed Change Based on Kullback-Leibler Divergence with a Gaussian Mixture Model.

Sensors (Basel, Switzerland)
Machining is a crucial constituent of the manufacturing industry, which has begun to transition from precision machinery to smart machinery. Particularly, the introduction of artificial intelligence into computer numerically controlled (CNC) machine ...

Bidirectionally self-normalizing neural networks.

Neural networks : the official journal of the International Neural Network Society
The problem of vanishing and exploding gradients has been a long-standing obstacle that hinders the effective training of neural networks. Despite various tricks and techniques that have been employed to alleviate the problem in practice, there still...

Statistically unbiased prediction enables accurate denoising of voltage imaging data.

Nature methods
Here we report SUPPORT (statistically unbiased prediction utilizing spatiotemporal information in imaging data), a self-supervised learning method for removing Poisson-Gaussian noise in voltage imaging data. SUPPORT is based on the insight that a pix...

The Deep Generative Decoder: MAP estimation of representations improves modelling of single-cell RNA data.

Bioinformatics (Oxford, England)
MOTIVATION: Learning low-dimensional representations of single-cell transcriptomics has become instrumental to its downstream analysis. The state of the art is currently represented by neural network models, such as variational autoencoders, which us...

Are you sure it's an artifact? Artifact detection and uncertainty quantification in histological images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Modern cancer diagnostics involves extracting tissue specimens from suspicious areas and conducting histotechnical procedures to prepare a digitized glass slide, called Whole Slide Image (WSI), for further examination. These procedures frequently int...

Frequency compensated diffusion model for real-scene dehazing.

Neural networks : the official journal of the International Neural Network Society
Due to distribution shift, deep learning based methods for image dehazing suffer from performance degradation when applied to real-world hazy images. In this paper, this study considers a dehazing framework based on conditional diffusion models for i...

An Unsupervised Machine Learning Approach for the Automatic Construction of Local Chemical Descriptors.

Journal of chemical information and modeling
Condensing the many physical variables defining a chemical system into a fixed-size array poses a significant challenge in the development of chemical Machine Learning (ML). Atom Centered Symmetry Functions (ACSFs) offer an intuitive featurization ap...

Enhancing deep learning pre-trained networks on diabetic retinopathy fundus photographs with SLIC-G.

Medical & biological engineering & computing
Diabetic retinopathy disease contains lesions (e.g., exudates, hemorrhages, and microaneurysms) that are minute to the naked eye. Determining the lesions at pixel level poses a challenge as each pixel does not reflect any semantic entities. Furthermo...