AIMC Topic: Neural Networks, Computer

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Efficient and Accurate Simulations of Vibrational and Electronic Spectra with Symmetry-Preserving Neural Network Models for Tensorial Properties.

The journal of physical chemistry. B
Machine learning has revolutionized the high-dimensional representations for molecular properties such as potential energy. However, there are scarce machine learning models targeting tensorial properties, which are rotationally covariant. Here, we p...

Data Augmentation for Motor Imagery Signal Classification Based on a Hybrid Neural Network.

Sensors (Basel, Switzerland)
As an important paradigm of spontaneous brain-computer interfaces (BCIs), motor imagery (MI) has been widely used in the fields of neurological rehabilitation and robot control. Recently, researchers have proposed various methods for feature extracti...

Personal identification with orthopantomography using simple convolutional neural networks: a preliminary study.

Scientific reports
Forensic dental examination has played an important role in personal identification (PI). However, PI has essentially been based on traditional visual comparisons of ante- and postmortem dental records and radiographs, and there is no globally accept...

Neural network-based supervised descent method for 2D electrical impedance tomography.

Physiological measurement
OBJECTIVE: In this work, we study the application of the neural network-based supervised descent method (NN-SDM) for 2D electrical impedance tomography.

Identifying COVID19 from Chest CT Images: A Deep Convolutional Neural Networks Based Approach.

Journal of healthcare engineering
Coronavirus Disease (COVID19) is a fast-spreading infectious disease that is currently causing a healthcare crisis around the world. Due to the current limitations of the reverse transcription-polymerase chain reaction (RT-PCR) based tests for detect...

Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes.

PloS one
In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before progressing to human trials. However, relating the results of animal and in vitro model exposures to r...

Real-time assessment of video images for esophageal squamous cell carcinoma invasion depth using artificial intelligence.

Journal of gastroenterology
BACKGROUND: Although optimal treatment of superficial esophageal squamous cell carcinoma (SCC) requires accurate evaluation of cancer invasion depth, the current process is rather subjective and may vary by observer. We, therefore, aimed to develop a...

Numerical simulation of deformed red blood cell by utilizing neural network approach and finite element analysis.

Computer methods in biomechanics and biomedical engineering
In order to have research on the deformation characteristics and mechanical properties of human red blood cells (RBCs), finite element models of RBC optical tweezers stretching and atomic force microscope (AFM) indentation were established. Non-linea...

Deep learning and level set approach for liver and tumor segmentation from CT scans.

Journal of applied clinical medical physics
PURPOSE: Segmentation of liver organ and tumors from computed tomography (CT) scans is an important task for hepatic surgical planning. Manual segmentation of liver and tumors is tedious, time-consuming, and biased to the clinician experience. Theref...

Cortical-like dynamics in recurrent circuits optimized for sampling-based probabilistic inference.

Nature neuroscience
Sensory cortices display a suite of ubiquitous dynamical features, such as ongoing noise variability, transient overshoots and oscillations, that have so far escaped a common, principled theoretical account. We developed a unifying model for these ph...