ArticlePeerJ. Computer science2019
A systematic review on literature-based discovery workflow.
Article in PeerJ. Computer science, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed.
- Enriched knowledge representation in biological fields: a case study of literature-based discovery in Alzheimer's disease.Journal of biomedical semantics · 2025Article
- Multi-objective optimization for smart cities: a systematic review of algorithms, challenges, and future directions.PeerJ. Computer science · 2025Review
- Mining impactful discoveries from the biomedical literature.BMC bioinformatics · 2024Article
- Serial KinderMiner (SKiM) discovers and annotates biomedical knowledge using co-occurrence and transformer models.BMC bioinformatics · 2023Article
- Literature-based discovery: addressing the issue of the subpar evaluation methodology.Bioinformatics (Oxford, England) · 2023Article
- Classification of Covid-19 misinformation on social media based on neuro-fuzzy and neural network: A systematic review.Neural computing & applications · 2023Article
- Non-Specific Low Back Pain, Dietary Salt Intake, and Posterior Lumbar Subcutaneous Edema.International journal of environmental research and public health · 2022Article
- Literature Mining of Disease Associated Noncoding RNA in the Omics Era.Molecules (Basel, Switzerland) · 2022Review
- Computational Literature-based Discovery for Natural Products Research: Current State and Future Prospects.Frontiers in bioinformatics · 2022Review
- Combining Literature Mining and Machine Learning for Predicting Biomedical Discoveries.Methods in molecular biology (Clifton, N.J.) · 2022Article
- MeSH and text-word search strategies: precision, recall, and their implications for library instruction.Journal of the Medical Library Association : JMLA · 2022Article
- PubMed-Scale Chemical Concept Embeddings Reconstruct Physical Protein Interaction Networks.Frontiers in research metrics and analytics · 2021Article
- Exploration of Shared Themes Between Food Security and Internet of Things Research Through Literature-Based Discovery.Frontiers in research metrics and analytics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As scientific publication rates increase, knowledge acquisition and the research development process have become more complex and time-consuming. Literature-Based Discovery (LBD), supporting automated knowledge discovery, helps facilitate this process by eliciting novel knowledge by analysing existing scientific literature. This systematic review provides a comprehensive overview of the LBD workflow by answering nine research questions related to the major components of the LBD workflow (i.e., input, process, output, and evaluation). With regards to the
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.