AIMC Topic: Computer Graphics

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Analyzing Learned Molecular Representations for Property Prediction.

Journal of chemical information and modeling
Advancements in neural machinery have led to a wide range of algorithmic solutions for molecular property prediction. Two classes of models in particular have yielded promising results: neural networks applied to computed molecular fingerprints or ex...

Detecting drug-drug interactions using artificial neural networks and classic graph similarity measures.

PloS one
Drug-drug interactions are preventable causes of medical injuries and often result in doctor and emergency room visits. Computational techniques can be used to predict potential drug-drug interactions. We approach the drug-drug interaction prediction...

A Literature Review: Geometric Methods and Their Applications in Human-Related Analysis.

Sensors (Basel, Switzerland)
Geometric features, such as the topological and manifold properties, are utilized to extract geometric properties. Geometric methods that exploit the applications of geometrics, e.g., geometric features, are widely used in computer graphics and compu...

Automatic segmentation of hyperreflective foci in OCT images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The leading cause of vision loss in the Western World is Age-related Macular Degeneration (AMD), but together with modern medicines, tracking the number of Hyperreflective Foci (HF) on Optical Coherence Tomography (OCT) imag...

A comparative study on feature selection for a risk prediction model for colorectal cancer.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Risk prediction models aim at identifying people at higher risk of developing a target disease. Feature selection is particularly important to improve the prediction model performance avoiding overfitting and to identify the...

Insights and approaches using deep learning to classify wildlife.

Scientific reports
The implementation of intelligent software to identify and classify objects and individuals in visual fields is a technology of growing importance to operatives in many fields, including wildlife conservation and management. To non-experts, the metho...

Classification of Polar Maps from Cardiac Perfusion Imaging with Graph-Convolutional Neural Networks.

Scientific reports
Myocardial perfusion imaging is a non-invasive imaging technique commonly used for the diagnosis of Coronary Artery Disease and is based on the injection of radiopharmaceutical tracers into the blood stream. The patient's heart is imaged while at res...

LDA Ensembles for Interactive Exploration and Categorization of Behaviors.

IEEE transactions on visualization and computer graphics
We define behavior as a set of actions performed by some actor during a period of time. We consider the problem of analyzing a large collection of behaviors by multiple actors, more specifically, identifying typical behaviors and spotting anomalous b...

Analysis of an evolutionary algorithm for complex fuzzy cognitive map learning based on graph theory metrics and output concepts.

Bio Systems
The fuzzy cognitive map (FCM) is an effective tool for modeling dynamic decision support systems. It describes the analyzed phenomenon in the form of key concepts and the causal connections between them. The main aspects of the building of the FCM mo...

DeepChemStable: Chemical Stability Prediction with an Attention-Based Graph Convolution Network.

Journal of chemical information and modeling
In the drug discovery process, unstable compounds in storage can lead to false positive or false negative bioassay conclusions. Prediction of the chemical stability of a compound by de novo methods is complex. Chemical instability prediction is commo...