AIMC Topic: Pattern Recognition, Automated

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BioDKG-DDI: predicting drug-drug interactions based on drug knowledge graph fusing biochemical information.

Briefings in functional genomics
The way of co-administration of drugs is a sensible strategy for treating complex diseases efficiently. Because of existing massive unknown interactions among drugs, predicting potential adverse drug-drug interactions (DDIs) accurately is promotive t...

Attention-based Knowledge Graph Representation Learning for Predicting Drug-drug Interactions.

Briefings in bioinformatics
Drug-drug interactions (DDIs) are known as the main cause of life-threatening adverse events, and their identification is a key task in drug development. Existing computational algorithms mainly solve this problem by using advanced representation lea...

Embedded AI system for interactive vision screen based on human action recognition.

The Review of scientific instruments
In recent years, vision screening has emerged globally for employment (on a yearly basis) within primary and high schools since myopia heavily affects school-aged children. However, this is a laborious and time-consuming task. This article proposes a...

DeepKG: an end-to-end deep learning-based workflow for biomedical knowledge graph extraction, optimization and applications.

Bioinformatics (Oxford, England)
SUMMARY: DeepKG is an end-to-end deep learning-based workflow that helps researchers automatically mine valuable knowledge in biomedical literature. Users can utilize it to establish customized knowledge graphs in specified domains, thus facilitating...

SumGNN: multi-typed drug interaction prediction via efficient knowledge graph summarization.

Bioinformatics (Oxford, England)
MOTIVATION: Thanks to the increasing availability of drug-drug interactions (DDI) datasets and large biomedical knowledge graphs (KGs), accurate detection of adverse DDI using machine learning models becomes possible. However, it remains largely an o...

Spatio-temporal continuous gesture recognition under degraded environments: performance comparison between 3D integral imaging (InIm) and RGB-D sensors.

Optics express
In this paper, we introduce a deep learning-based spatio-temporal continuous human gesture recognition algorithm under degraded conditions using three-dimensional (3D) integral imaging. The proposed system is shown as an efficient continuous human ge...

Drug-drug interaction prediction with Wasserstein Adversarial Autoencoder-based knowledge graph embeddings.

Briefings in bioinformatics
An interaction between pharmacological agents can trigger unexpected adverse events. Capturing richer and more comprehensive information about drug-drug interactions (DDIs) is one of the key tasks in public health and drug development. Recently, seve...

Performance of SURF and SIFT Keypoints for the Automated Differentiation of Abnormality in Chest Radiographs.

Studies in health technology and informatics
In this work, automated abnormality detection using keypoint information from Speeded-Up Robust feature (SURF) and Scale Invariant Feature Transform (SIFT) descriptors in chest Radiographic (CR) images is investigated and compared. Computerized image...

Towards a Knowledge Graph-Based Explainable Decision Support System in Healthcare.

Studies in health technology and informatics
The decisions derived from AI-based clinical decision support systems should be explainable and transparent so that the healthcare professionals can understand the rationale behind the predictions. To improve the explanations, knowledge graphs are a ...