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Knowledge Bases

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NDDRF: A risk factor knowledgebase for personalized prevention of neurodegenerative diseases.

Journal of advanced research
INTRODUCTION: Neurodegenerative diseases (NDDs) are a series of chronic diseases, which are associated with progressive loss of neuronal structure or function. The complex etiologies of the NDDs remain unclear, thus the prevention and early diagnosis...

Modern computational intelligence based drug repurposing for diabetes epidemic.

Diabetes & metabolic syndrome
BACKGROUND AND AIM: Objectives are to explore recent advances in discovery of new antidiabetic agents using repurposing strategies and to discuss modern technologies used for drug repurposing highlighting diabetic specific web portal.

Biomedical Knowledge Graphs Construction From Conditional Statements.

IEEE/ACM transactions on computational biology and bioinformatics
Conditions play an essential role in biomedical statements. However, existing biomedical knowledge graphs (BioKGs) only focus on factual knowledge, organized as a flat relational network of biomedical concepts. These BioKGs ignore the conditions of t...

Improving the recall of biomedical named entity recognition with label re-correction and knowledge distillation.

BMC bioinformatics
BACKGROUND: Biomedical named entity recognition is one of the most essential tasks in biomedical information extraction. Previous studies suffer from inadequate annotated datasets, especially the limited knowledge contained in them.

Causal relationship extraction from biomedical text using deep neural models: A comprehensive survey.

Journal of biomedical informatics
The identification of causal relationships between events or entities within biomedical texts is of great importance for creating scientific knowledge bases and is also a fundamental natural language processing (NLP) task. A causal (cause-effect) rel...

Explainable artificial intelligence in high-throughput drug repositioning for subgroup stratifications with interventionable potential.

Journal of biomedical informatics
Enabling precision medicine requires developing robust patient stratification methods as well as drugs tailored to homogeneous subgroups of patients from a heterogeneous population. Developing de novo drugs is expensive and time consuming with an ult...

Inaccuracies in Google's Health-Based Knowledge Panels Perpetuate Widespread Misconceptions Involving Infectious Disease Transmission.

The American journal of tropical medicine and hygiene
Google health-based Knowledge Panels were designed to provide users with high-quality basic medical information on a specific condition. However, any errors contained within Knowledge Panels could result in the widespread distribution of inaccurate h...

Quantifying the separability of data classes in neural networks.

Neural networks : the official journal of the International Neural Network Society
We introduce the Generalized Discrimination Value (GDV) that measures, in a non-invasive manner, how well different data classes separate in each given layer of an artificial neural network. It turns out that, at the end of the training period, the G...

A knowledge base of clinical trial eligibility criteria.

Journal of biomedical informatics
OBJECTIVE: We present the Clinical Trial Knowledge Base, a regularly updated knowledge base of discrete clinical trial eligibility criteria equipped with a web-based user interface for querying and aggregate analysis of common eligibility criteria.

Evaluation of a highly refined prediction model in knowledge-based volumetric modulated arc therapy planning for cervical cancer.

Radiation oncology (London, England)
BACKGROUND AND PURPOSE: To explore whether a highly refined dose volume histograms (DVH) prediction model can improve the accuracy and reliability of knowledge-based volumetric modulated arc therapy (VMAT) planning for cervical cancer.