AIMC Topic: Pattern Recognition, Automated

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Knowledge Graphs and Their Applications in Drug Discovery.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2024
Knowledge graphs represent information in the form of entities and relationships between those entities. Such a representation has multiple potential applications in drug discovery, including democratizing access to biomedical data, contextualizing o...
Artificial Intelligence Machine Learning Drug Discovery Pattern Recognition, Automated
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AI beats human sleuth at finding problematic images in research papers.

Nature Oct 1, 2023
Humans Artificial Intelligence Research Report Pattern Recognition, Automated Photography
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DKADE: a novel framework based on deep learning and knowledge graph for identifying adverse drug events and related medications.

Briefings in bioinformatics Jul 20, 2023
Adverse drug events (ADEs) are common in clinical practice and can cause significant harm to patients and increase resource use. Natural language processing (NLP) has been applied to automate ADE detection, but NLP systems become less adaptable when ...
Humans Deep Learning Natural Language Processing Drug-Related Side Effects and Adverse Reactions Semantics Pattern Recognition, Automated
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KG-Hub-building and exchanging biological knowledge graphs.

Bioinformatics (Oxford, England) Jul 1, 2023
MOTIVATION: Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of KGs is...
Humans Machine Learning COVID-19 Biological Ontologies Pattern Recognition, Automated Rare Diseases
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TRSRD: a database for research on risky substances in tea using natural language processing and knowledge graph-based techniques.

Database : the journal of biological databases and curation May 9, 2023
During the production and processing of tea, harmful substances are often introduced. However, they have never been systematically integrated, and it is impossible to understand the harmful substances that may be introduced during tea production and ...
Databases, Factual Tea Natural Language Processing Pattern Recognition, Automated Knowledge
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A lightweight CNN-based knowledge graph embedding model with channel attention for link prediction.

Mathematical biosciences and engineering : MBE Mar 21, 2023
Knowledge graph (KG) embedding is to embed the entities and relations of a KG into a low-dimensional continuous vector space while preserving the intrinsic semantic associations between entities and relations. One of the most important applications o...
Neural Networks, Computer Semantics Pattern Recognition, Automated
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A multimodal fusion enabled ensemble approach for human activity recognition in smart homes.

Health informatics journal Jan 1, 2023
How to deal with multi-modality data from different types of devices is a challenging issue for accurate recognition of human activities in a smart environment. In this paper, we propose a multimodal fusion enabled ensemble approach. Firstly, useful ...
Humans Algorithms Support Vector Machine Fuzzy Logic Pattern Recognition, Automated Human Activities
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SVM classifier of cervical histopathology images based on texture and morphological features.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2023
BACKGROUND: Cervical histopathology image classification is a crucial indicator in cervical biopsy results.
Humans Female Uterine Cervical Neoplasms Support Vector Machine Image Interpretation, Computer-Assisted Pattern Recognition, Automated
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A review of biomedical datasets relating to drug discovery: a knowledge graph perspective.

Briefings in bioinformatics Nov 19, 2022
Drug discovery and development is a complex and costly process. Machine learning approaches are being investigated to help improve the effectiveness and speed of multiple stages of the drug discovery pipeline. Of these, those that use Knowledge Graph...
Machine Learning Drug Discovery Information Storage and Retrieval Pattern Recognition, Automated Knowledge
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Implications of topological imbalance for representation learning on biomedical knowledge graphs.

Briefings in bioinformatics Sep 20, 2022
Adoption of recently developed methods from machine learning has given rise to creation of drug-discovery knowledge graphs (KGs) that utilize the interconnected nature of the domain. Graph-based modelling of the data, combined with KG embedding (KGE)...
Machine Learning Pattern Recognition, Automated Knowledge
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