AIMC Topic: Knowledge Bases

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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
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 ...

Improving preliminary clinical diagnosis accuracy through knowledge filtering techniques in consultation dialogues.

Computer methods and programs in biomedicine
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...

CanVaxKB: a web-based cancer vaccine knowledgebase.

NAR cancer
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...

Comprehensive Review of Drug-Drug Interaction Prediction Based on Machine Learning: Current Status, Challenges, and Opportunities.

Journal of chemical information and modeling
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...

Assessing resolvability, parsability, and consistency of RDF resources: a use case in rare diseases.

Journal of biomedical semantics
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...

FIT-graph: A multi-grained evolutionary graph based framework for disease diagnosis.

Artificial intelligence in medicine
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...

Computational prediction of complex cationic rearrangement outcomes.

Nature
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...

A knowledge graph-based data harmonization framework for secondary data reuse.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The adoption of new technologies in clinical care systems has propitiated the availability of a great amount of valuable data. However, this data is usually heterogeneous, requiring its harmonization to be integrated and ana...

The smarty4covid dataset and knowledge base as a framework for interpretable physiological audio data analysis.

Scientific data
Harnessing the power of Artificial Intelligence (AI) and m-health towards detecting new bio-markers indicative of the onset and progress of respiratory abnormalities/conditions has greatly attracted the scientific and research interest especially dur...

ChatGPT: a tool for scientific writing or a threat to integrity?

The British journal of radiology
The use of ChatGPT as a tool for writing and knowledge integration raises concerns about the potential for its use to replace critical thinking and academic writing skills. While ChatGPT can assist in generating text and suggesting appropriate langua...