AIMC Topic: Neural Networks, Computer

Clear Filters Showing 18881 to 18890 of 31376 articles

DeepPheno: Predicting single gene loss-of-function phenotypes using an ontology-aware hierarchical classifier.

PLoS computational biology
Predicting the phenotypes resulting from molecular perturbations is one of the key challenges in genetics. Both forward and reverse genetic screen are employed to identify the molecular mechanisms underlying phenotypes and disease, and these resulted...

Driver Fatigue Detection Based on Convolutional Neural Networks Using EM-CNN.

Computational intelligence and neuroscience
With a focus on fatigue driving detection research, a fully automated driver fatigue status detection algorithm using driving images is proposed. In the proposed algorithm, the multitask cascaded convolutional network (MTCNN) architecture is employed...

Development of LC-MS/MS determination method and backpropagation artificial neural networks pharmacokinetic model of febuxostat in healthy subjects.

Journal of clinical pharmacy and therapeutics
WHAT IS KNOWN AND OBJECTIVE: Febuxostat is a well-known drug for treating hyperuricemia and gout. The published methods for determination of febuxostat in human plasma might be unsuitable for high-throughput determination and widespread application. ...

Deep learning for the prediction of treatment response in depression.

Journal of affective disorders
BACKGROUND: Mood disorders are characterized by heterogeneity in severity, symptoms and treatment response. The possibility of selecting the correct therapy on the basis of patient-specific biomarker may be a considerable step towards personalized ps...

Hysteresis Modulation on Van der Waals-Based Ferroelectric Field-Effect Transistor by Interfacial Passivation Technique and Its Application in Optic Neural Networks.

Small (Weinheim an der Bergstrasse, Germany)
2D semiconductor-based ferroelectric field effect transistors (FeFETs) have been considered as a promising artificial synaptic device for implementation of neuromorphic computing systems. However, an inevitable problem, interface traps at the 2D semi...

Deep learning to predict elevated pulmonary artery pressure in patients with suspected pulmonary hypertension using standard chest X ray.

Scientific reports
Accurate diagnosis of pulmonary hypertension (PH) is crucial to ensure that patients receive timely treatment. We hypothesized that application of artificial intelligence (AI) to the chest X-ray (CXR) could identify elevated pulmonary artery pressure...

Automatic classification and segmentation of single-molecule fluorescence time traces with deep learning.

Nature communications
Traces from single-molecule fluorescence microscopy (SMFM) experiments exhibit photophysical artifacts that typically necessitate human expert screening, which is time-consuming and introduces potential for user-dependent expectation bias. Here, we u...

Robust facial landmark detection by cross-order cross-semantic deep network.

Neural networks : the official journal of the International Neural Network Society
Recently, convolutional neural networks (CNNs)-based facial landmark detection methods have achieved great success. However, most of existing CNN-based facial landmark detection methods have not attempted to activate multiple correlated facial parts ...

Artificial intelligence in oral and maxillofacial radiology: what is currently possible?

Dento maxillo facial radiology
Artificial intelligence, which has been actively applied in a broad range of industries in recent years, is an active area of interest for many researchers. Dentistry is no exception to this trend, and the applications of artificial intelligence are ...

Multi-task convolutional neural network-based design of radio frequency pulse and the accompanying gradients for magnetic resonance imaging.

NMR in biomedicine
Modern MRI systems usually load the predesigned RFs and the accompanying gradients during clinical scans, with minimal adaption to the specific requirements of each scan. Here, we describe a neural network-based method for real-time design of excitat...