AIMC Topic: Knowledge Bases

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Bayesian-knowledge driven ontologies: A framework for fusion of semantic knowledge under uncertainty and incompleteness.

PloS one Mar 27, 2024
The modeling of uncertain information is an open problem in ontology research and is a theoretical obstacle to creating a truly semantic web. Currently, ontologies often do not model uncertainty, so stochastic subject matter must either be normalized...
Semantics Bayes Theorem Biological Ontologies Knowledge Bases Logic Uncertainty
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Enriching the FIDEO ontology with food-drug interactions from online knowledge sources.

Journal of biomedical semantics Mar 4, 2024
The increasing number of articles on adverse interactions that may occur when specific foods are consumed with certain drugs makes it difficult to keep up with the latest findings. Conflicting information is available in the scientific literature and...
Knowledge Bases Food-Drug Interactions
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dbCRAF: a curated knowledgebase for regulation of radiation response in human cancer.

NAR cancer Feb 24, 2024
Radiation therapy (RT) is one of the primary treatment modalities of cancer, with 40-60% of cancer patients benefiting from RT during their treatment course. The intrinsic radiosensitivity or acquired radioresistance of tumor cells would affect the r...
Humans Gene Expression Regulation, Neoplastic Databases, Genetic Knowledge Bases Radiation Tolerance Neoplasms Computational Biology Prognosis
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Enabling personalised disease diagnosis by combining a patient's time-specific gene expression profile with a biomedical knowledge base.

BMC bioinformatics Feb 7, 2024
BACKGROUND: Recent developments in the domain of biomedical knowledge bases (KBs) open up new ways to exploit biomedical knowledge that is available in the form of KBs. Significant work has been done in the direction of biomedical KB creation and KB ...
Machine Learning Algorithms Humans Transcriptome Knowledge Bases
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Improving preliminary clinical diagnosis accuracy through knowledge filtering techniques in consultation dialogues.

Computer methods and programs in biomedicine Jan 30, 2024
BACKGROUND AND OBJECTIVE: Symptom descriptions by ordinary people are often inaccurate or vague when seeking medical advice, which often leads to inaccurate preliminary clinical diagnoses. To address this issue, we propose a deep learning model named...
Natural Language Processing Benchmarking Knowledge Bases Referral and Consultation Language United States Humans
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CanVaxKB: a web-based cancer vaccine knowledgebase.

NAR cancer Jan 9, 2024
Cancer vaccines have been increasingly studied and developed to prevent or treat various types of cancers. To systematically survey and analyze different reported cancer vaccines, we developed CanVaxKB (https://violinet.org/canvaxkb), the first web-b...
Neoplasms Cancer Vaccines Humans Knowledge Bases Antigens, Neoplasm Internet
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Comprehensive Review of Drug-Drug Interaction Prediction Based on Machine Learning: Current Status, Challenges, and Opportunities.

Journal of chemical information and modeling Dec 22, 2023
Detecting drug-drug interactions (DDIs) is an essential step in drug development and drug administration. Given the shortcomings of current experimental methods, the machine learning (ML) approach has become a reliable alternative, attracting extensi...
Drug Interactions Knowledge Bases Databases, Factual Pharmaceutical Preparations Machine Learning
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Assessing resolvability, parsability, and consistency of RDF resources: a use case in rare diseases.

Journal of biomedical semantics Dec 5, 2023
INTRODUCTION: Healthcare data and the knowledge gleaned from it play a key role in improving the health of current and future patients. These knowledge sources are regularly represented as 'linked' resources based on the Resource Description Framewor...
Humans Knowledge Bases Rare Diseases
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FIT-graph: A multi-grained evolutionary graph based framework for disease diagnosis.

Artificial intelligence in medicine Nov 30, 2023
Early assessment, with the help of machine learning methods, can aid clinicians in optimizing the diagnosis and treatment process, allowing patients to receive critical treatment time. Due to the advantages of effective information organization and i...
Knowledge Bases Machine Learning Humans Algorithms
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Computational prediction of complex cationic rearrangement outcomes.

Nature Nov 15, 2023
Recent years have seen revived interest in computer-assisted organic synthesis. The use of reaction- and neural-network algorithms that can plan multistep synthetic pathways have revolutionized this field, including examples leading to advanced natur...
Knowledge Bases Chemistry Techniques, Synthetic Biological Products Neural Networks, Computer Terpenes Algorithms Cations Reproducibility of Results Cyclization Solutions
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