AIMC Topic: Neural Networks, Computer

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Generative Recurrent Networks for De Novo Drug Design.

Molecular informatics
Generative artificial intelligence models present a fresh approach to chemogenomics and de novo drug design, as they provide researchers with the ability to narrow down their search of the chemical space and focus on regions of interest. We present a...

A hybrid classifier based on nonlinear-PCA and deep belief networks with applications in dysphagia diagnosis.

Computer assisted surgery (Abingdon, England)
Traditional dysphagia prescreening diagnostic methods require doctors specialists to give patients a total score based on a water swallow test scale. This method is limited by the high dimensionality of the diagnostic elements in the water swallow te...

Multi-categorical deep learning neural network to classify retinal images: A pilot study employing small database.

PloS one
Deep learning emerges as a powerful tool for analyzing medical images. Retinal disease detection by using computer-aided diagnosis from fundus image has emerged as a new method. We applied deep learning convolutional neural network by using MatConvNe...

Flood susceptibility assessment in Hengfeng area coupling adaptive neuro-fuzzy inference system with genetic algorithm and differential evolution.

The Science of the total environment
Floods are among Earth's most common natural hazards, and they cause major economic losses and seriously affect peoples' lives and health. This paper addresses the development of a flood susceptibility assessment that uses intelligent techniques and ...

Neural network dose models for knowledge-based planning in pancreatic SBRT.

Medical physics
PURPOSE: Stereotactic body radiation therapy (SBRT) for pancreatic cancer requires a skillful approach to deliver ablative doses to the tumor while limiting dose to the highly sensitive duodenum, stomach, and small bowel. Here, we develop knowledge-b...

CNNs-Based RGB-D Saliency Detection via Cross-View Transfer and Multiview Fusion.

IEEE transactions on cybernetics
Salient object detection from RGB-D images aims to utilize both the depth view and RGB view to automatically localize objects of human interest in the scene. Although a few earlier efforts have been devoted to the study of this paper in recent years,...

A deep belief network with PLSR for nonlinear system modeling.

Neural networks : the official journal of the International Neural Network Society
Nonlinear system modeling plays an important role in practical engineering, and deep learning-based deep belief network (DBN) is now popular in nonlinear system modeling and identification because of the strong learning ability. However, the existing...

Supervised learning methods for pathological arterial pulse wave differentiation: A SVM and neural networks approach.

International journal of medical informatics
OBJECTIVE: The main goal of this study was to develop an automatic method based on supervised learning methods, able to distinguish healthy from pathologic arterial pulse wave (APW), and those two from noisy waveforms (non-relevant segments of the si...

Use of a Neural Net to Model the Impact of Optical Coherence Tomography Abnormalities on Vision in Age-related Macular Degeneration.

American journal of ophthalmology
PURPOSE: To develop a neural network for the estimation of visual acuity from optical coherence tomography (OCT) images of patients with neovascular age-related macular degeneration (AMD) and to demonstrate its use to model the impact of specific con...

Parallel Distributed Processing Theory in the Age of Deep Networks.

Trends in cognitive sciences
Parallel distributed processing (PDP) models in psychology are the precursors of deep networks used in computer science. However, only PDP models are associated with two core psychological claims, namely that all knowledge is coded in a distributed f...