AI Medical Compendium Topic:
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Graph Convolutional Networks for Drug Response Prediction.

IEEE/ACM transactions on computational biology and bioinformatics
BACKGROUND: Drug response prediction is an important problem in computational personalized medicine. Many machine-learning-based methods, especially deep learning-based ones, have been proposed for this task. However, these methods often represent th...

PDGNet: Predicting Disease Genes Using a Deep Neural Network With Multi-View Features.

IEEE/ACM transactions on computational biology and bioinformatics
The knowledge of phenotype-genotype associations is crucial for the understanding of disease mechanisms. Numerous studies have focused on developing efficient and accurate computing approaches to predict disease genes. However, owing to the sparsenes...

Artificial Intelligence: A New Diagnostic Software in Dentistry: A Preliminary Performance Diagnostic Study.

International journal of environmental research and public health
BACKGROUND: Artificial intelligence (AI) has taken hold in public health because more and more people are looking to make a diagnosis using technology that allows them to work faster and more accurately, reducing costs and the number of medical error...

Automatic Target Detection from Satellite Imagery Using Machine Learning.

Sensors (Basel, Switzerland)
Object detection is a vital step in satellite imagery-based computer vision applications such as precision agriculture, urban planning and defense applications. In satellite imagery, object detection is a very complicated task due to various reasons ...

Automatic mapping of multiplexed social receptive fields by deep learning and GPU-accelerated 3D videography.

Nature communications
Social interactions powerfully impact the brain and the body, but high-resolution descriptions of these important physical interactions and their neural correlates are lacking. Currently, most studies rely on labor-intensive methods such as manual an...

MDL-CPI: Multi-view deep learning model for compound-protein interaction prediction.

Methods (San Diego, Calif.)
Elucidating the mechanisms of Compound-Protein Interactions (CPIs) plays an essential role in drug discovery and development. Many computational efforts have been done to accelerate the development of this field. However, the current predictive perfo...

Machine Learning Techniques for Increasing Efficiency of the Robot's Sensor and Control Information Processing.

Sensors (Basel, Switzerland)
Real-time systems are widely used in industry, including technological process control systems, industrial automation systems, SCADA systems, testing, and measuring equipment, and robotics. The efficiency of executing an intelligent robot's mission i...

Instance segmentation convolutional neural network based on multi-scale attention mechanism.

PloS one
Instance segmentation is more challenging and difficult than object detection and semantic segmentation. It paves the way for the realization of a complete scene understanding, and has been widely used in robotics, automatic driving, medical care, an...

AIME: Autoencoder-based integrative multi-omics data embedding that allows for confounder adjustments.

PLoS computational biology
In the integrative analyses of omics data, it is often of interest to extract data representation from one data type that best reflect its relations with another data type. This task is traditionally fulfilled by linear methods such as canonical corr...

Robot System Assistant (RoSA): Towards Intuitive Multi-Modal and Multi-Device Human-Robot Interaction.

Sensors (Basel, Switzerland)
This paper presents an implementation of RoSA, a Robot System Assistant, for safe and intuitive human-machine interaction. The interaction modalities were chosen and previously reviewed using a Wizard of Oz study emphasizing a strong propensity for s...