AIMC Topic: Neural Networks, Computer

Clear Filters Showing 24061 to 24070 of 31376 articles

Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

Cell chemical biology
In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, who...

Prediction of Overall Survival and Novel Classification of Patients with Gastric Cancer Using the Survival Recurrent Network.

Annals of surgical oncology
BACKGROUND: Artificial neural networks (ANNs) have been applied to many prediction and classification problems, and could also be used to develop a prediction model of survival outcomes for cancer patients.

Deep learning with convolutional neural network in radiology.

Japanese journal of radiology
Deep learning with a convolutional neural network (CNN) is gaining attention recently for its high performance in image recognition. Images themselves can be utilized in a learning process with this technique, and feature extraction in advance of the...

A modified artificial neural network based prediction technique for tropospheric radio refractivity.

PloS one
Radio refractivity plays a significant role in the development and design of radio systems for attaining the best level of performance. Refractivity in the troposphere is one of the features affecting electromagnetic waves, and hence the communicatio...

Segmentation of Intra-Retinal Cysts From Optical Coherence Tomography Images Using a Fully Convolutional Neural Network Model.

IEEE journal of biomedical and health informatics
Optical coherence tomography (OCT) is an imaging modality that is used extensively for ophthalmic diagnosis, near-histological visualization, and quantification of retinal abnormalities such as cysts, exudates, retinal layer disorganization, etc. Int...

AxonDeepSeg: automatic axon and myelin segmentation from microscopy data using convolutional neural networks.

Scientific reports
Segmentation of axon and myelin from microscopy images of the nervous system provides useful quantitative information about the tissue microstructure, such as axon density and myelin thickness. This could be used for instance to document cell morphom...

A symbolic network-based nonlinear theory for dynamical systems observability.

Scientific reports
When the state of the whole reaction network can be inferred by just measuring the dynamics of a limited set of nodes the system is said to be fully observable. However, as the number of all possible combinations of measured variables and time deriva...

Deep Residual Network Predicts Cortical Representation and Organization of Visual Features for Rapid Categorization.

Scientific reports
The brain represents visual objects with topographic cortical patterns. To address how distributed visual representations enable object categorization, we established predictive encoding models based on a deep residual network, and trained them to pr...

Artificial Intelligence, Machine Learning, Deep Learning, and Cognitive Computing: What Do These Terms Mean and How Will They Impact Health Care?

The Journal of arthroplasty
This article was presented at the 2017 annual meeting of the American Association of Hip and Knee Surgeons to introduce the members gathered as the audience to the concepts behind artificial intelligence (AI) and the applications that AI can have in ...

Multi-channel multi-scale fully convolutional network for 3D perivascular spaces segmentation in 7T MR images.

Medical image analysis
Accurate segmentation of perivascular spaces (PVSs) is an important step for quantitative study of PVS morphology. However, since PVSs are the thin tubular structures with relatively low contrast and also the number of PVSs is often large, it is chal...