AI Medical Compendium Topic

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Analysis of Expression Pattern of snoRNAs in Different Cancer Types with Machine Learning Algorithms.

International journal of molecular sciences
Small nucleolar RNAs (snoRNAs) are a new type of functional small RNAs involved in the chemical modifications of rRNAs, tRNAs, and small nuclear RNAs. It is reported that they play important roles in tumorigenesis via various regulatory modes. snoRNA...

A new application of radioactive particle tracking using MCNPX code and artificial neural network.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
Stirrers and mixers are highly used in chemical, food, pharmaceutical, cosmetic, concrete industries and others. During the fabrication process, the equipment may fail to appropriately stir or mix the solution. Besides that, it is also important to d...

A deep learning approach to estimation of subject-level bias and variance in high angular resolution diffusion imaging.

Magnetic resonance imaging
The ability to evaluate empirical diffusion MRI acquisitions for quality and to correct the resulting imaging metrics allows for improved inference and increased replicability. Previous work has shown promise for estimation of bias and variance of ge...

Patient-attentive sequential strategy for perimetry-based visual field acquisition.

Medical image analysis
Perimetry is a non-invasive clinical psychometric examination used for diagnosing ophthalmic and neurological conditions. At its core, perimetry relies on a subject pressing a button whenever they see a visual stimulus within their field of view. Thi...

GuacaMol: Benchmarking Models for de Novo Molecular Design.

Journal of chemical information and modeling
De novo design seeks to generate molecules with required property profiles by virtual design-make-test cycles. With the emergence of deep learning and neural generative models in many application areas, models for molecular design based on neural net...

Machine Learning Identifies Chemical Characteristics That Promote Enzyme Catalysis.

Journal of the American Chemical Society
Despite tremendous progress in understanding and engineering enzymes, knowledge of how enzyme structures and their dynamics induce observed catalytic properties is incomplete, and capabilities to engineer enzymes fall far short of industrial needs. H...

Dreaming neural networks: Forgetting spurious memories and reinforcing pure ones.

Neural networks : the official journal of the International Neural Network Society
The standard Hopfield model for associative neural networks accounts for biological Hebbian learning and acts as the harmonic oscillator for pattern recognition, however its maximal storage capacity is α∼0.14, far from the theoretical bound for symme...

Physiological interference reduction for near infrared spectroscopy brain activity measurement based on recursive least squares adaptive filtering and least squares support vector machines.

Computer assisted surgery (Abingdon, England)
Near infrared spectroscopy is the promising and noninvasive technique that can be used to detect the brain functional activation by monitoring the concentration alternations in the haemodynamic concentration. The acquired NIRS signals are commonly co...

From research to clinic: A sensor reduction method for high-density EEG neurofeedback systems.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: To accurately deliver a source-estimated neurofeedback (NF) signal developed on a 128-sensors EEG system on a reduced 32-sensors EEG system.

RNA3DCNN: Local and global quality assessments of RNA 3D structures using 3D deep convolutional neural networks.

PLoS computational biology
Quality assessment is essential for the computational prediction and design of RNA tertiary structures. To date, several knowledge-based statistical potentials have been proposed and proved to be effective in identifying native and near-native RNA st...