Objective: To select, present, and summarize the best papers in the field of Knowledge Representation and Management (KRM) published in 2019.
Methods: A comprehensive and standardized review of the biomedical informatics literature was performed to select the most interesting papers of KRM published in 2019, based on PubMed and ISI Web Of Knowledge queries.
Results: Four best papers were selected among 1,189 publications retrieved, following the usual International Medical Informatics Association Yearbook reviewing process. In 2019, research areas covered by pre-selected papers were represented by the design of semantic resources (methods, visualization, curation) and the application of semantic representations for the integration/enrichment of biomedical data. Besides new ontologies and sound methodological guidance to rethink knowledge bases design, we observed large scale applications, promising results for phenotypes characterization, semantic-aware machine learning solutions for biomedical data analysis, and semantic provenance information representations for scientific reproducibility evaluation.
Conclusion: In the KRM selection for 2019, research on knowledge representation demonstrated significant contributions both in the design and in the application of semantic resources. Semantic representations serve a great variety of applications across many medical domains, with actionable results.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7442529 | PMC |
| http://dx.doi.org/10.1055/s-0040-1702010 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Thoughts and thinkers: On the complementarity between objects and processes.
Phys Life Rev
January 2025
Allen Discovery Center at Tufts University, Medford, MA 02155, USA; Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA 02115, USA.
We argue that "processes versus objects" is not a useful dichotomy. There is, instead, substantial theoretical utility in viewing "objects" and "processes" as complementary ways of describing persistence through time, and hence the possibility of observation and manipulation. This way of thinking highlights the role of memory as an essential resource for observation, and makes it clear that "memory" and "time" are also mutually inter-defined, complementary concepts.
View Article and Find Full Text PDFMDA-DETR: Enhancing Offending Animal Detection with Multi-Channel Attention and Multi-Scale Feature Aggregation.
Animals (Basel)
January 2025
School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China.
Conflicts between humans and animals in agricultural and settlement areas have recently increased, resulting in significant resource loss and risks to human and animal lives. This growing issue presents a global challenge. This paper addresses the detection and identification of offending animals, particularly in obscured or blurry nighttime images.
View Article and Find Full Text PDFLow-resource MobileBERT for emotion recognition in imbalanced text datasets mitigating challenges with limited resources.
PLoS One
January 2025
Department of Computer Science, GC Women University Sialkot, Sialkot, Pakistan.
Modern dialogue systems rely on emotion recognition in conversation (ERC) as a core element enabling empathetic and human-like interactions. However, the weak correlation between emotions and semantics poses significant challenges to emotion recognition in dialogue. Semantically similar utterances can express different types of emotions, depending on the context or speaker.
View Article and Find Full Text PDFRobust Automated Harmonization of Heterogeneous Data Through Ensemble Machine Learning: Algorithm Development and Validation Study.
JMIR Med Inform
January 2025
Department of Biostatistics & Bioinformatics, Duke University, Durham, NC, United States.
Background: Cohort studies contain rich clinical data across large and diverse patient populations and are a common source of observational data for clinical research. Because large scale cohort studies are both time and resource intensive, one alternative is to harmonize data from existing cohorts through multicohort studies. However, given differences in variable encoding, accurate variable harmonization is difficult.
View Article and Find Full Text PDFGrammar-constrained decoding for structured information extraction with fine-tuned generative models applied to clinical trial abstracts.
Front Artif Intell
January 2025
Center for Cognitive Interaction Technology (CITEC), Technical Faculty, Bielefeld University, Bielefeld, Germany.
Background: In the field of structured information extraction, there are typically semantic and syntactic constraints on the output of information extraction (IE) systems. These constraints, however, can typically not be guaranteed using standard (fine-tuned) encoder-decoder architectures. This has led to the development of constrained decoding approaches which allow, e.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!