AI Medical Compendium Topic:
Semantics

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Graph Attention Feature Fusion Network for ALS Point Cloud Classification.

Sensors (Basel, Switzerland)
Classification is a fundamental task for airborne laser scanning (ALS) point cloud processing and applications. This task is challenging due to outdoor scenes with high complexity and point clouds with irregular distribution. Many existing methods ba...

ConAnomaly: Content-Based Anomaly Detection for System Logs.

Sensors (Basel, Switzerland)
Enterprise systems typically produce a large number of logs to record runtime states and important events. Log anomaly detection is efficient for business management and system maintenance. Most existing log-based anomaly detection methods use log pa...

Depth Estimation from Light Field Geometry Using Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Depth estimation based on light field imaging is a new methodology that has succeeded the traditional binocular stereo matching and depth from monocular images. Significant progress has been made in light-field depth estimation. Nevertheless, the bal...

Relation classification via BERT with piecewise convolution and focal loss.

PloS one
Recent relation extraction models' architecture are evolved from the shallow neural networks to natural language model, such as convolutional neural networks or recurrent neural networks to Bert. However, these methods did not consider the semantic i...

Dual coding of knowledge in the human brain.

Trends in cognitive sciences
How does the human brain code knowledge about the world? While disciplines such as artificial intelligence represent world knowledge based on human language, neurocognitive models of knowledge have been dominated by sensory embodiment, in which knowl...

Neural Network-Based Mapping Mining of Image Style Transfer in Big Data Systems.

Computational intelligence and neuroscience
Image style transfer can realize the mutual transfer between different styles of images and is an essential application for big data systems. The use of neural network-based image data mining technology can effectively mine the useful information in ...

Efficient, high-performance semantic segmentation using multi-scale feature extraction.

PloS one
The success of deep learning in recent years has arguably been driven by the availability of large datasets for training powerful predictive algorithms. In medical applications however, the sensitive nature of the data limits the collection and excha...

The Growing Role for Semantic Segmentation in Urology.

European urology focus
As the quantity and quality of cross-sectional imaging data increase, it is important to be able to make efficient use of the information. Semantic segmentation is an emerging technology that promises to improve the speed, reproducibility, and accura...

Unveiling functions of the visual cortex using task-specific deep neural networks.

PLoS computational biology
The human visual cortex enables visual perception through a cascade of hierarchical computations in cortical regions with distinct functionalities. Here, we introduce an AI-driven approach to discover the functional mapping of the visual cortex. We r...

Improving broad-coverage medical entity linking with semantic type prediction and large-scale datasets.

Journal of biomedical informatics
OBJECTIVES: Biomedical natural language processing tools are increasingly being applied for broad-coverage information extraction-extracting medical information of all types in a scientific document or a clinical note. In such broad-coverage settings...