AIMC Topic: Metadata

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The Ontology for Biomedical Investigations.

PloS one
The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide...

Ontology-Based Search of Genomic Metadata.

IEEE/ACM transactions on computational biology and bioinformatics
The Encyclopedia of DNA Elements (ENCODE) is a huge and still expanding public repository of more than 4,000 experiments and 25,000 data files, assembled by a large international consortium since 2007; unknown biological knowledge can be extracted fr...

Applying AI to Support Categorization of Heterogeneous Epidemiological Datasets.

Studies in health technology and informatics
The significance of Findable, Accessible, Interoperable, and Reusable (FAIR) data is increasing, particularly in the context of enhancing data reuse in research. The National Research Data Infrastructure for Personal Health Data (NFDI4Health) aims to...

Perceptual and technical barriers in sharing and formatting metadata accompanying omics studies.

Cell genomics
Metadata, or "data about data," is essential for organizing, understanding, and managing large-scale omics datasets. It enhances data discovery, integration, and interpretation, enabling reproducibility, reusability, and secondary analysis. However, ...

The text2term tool to map free-text descriptions of biomedical terms to ontologies.

Database : the journal of biological databases and curation
There is an ongoing need for scalable tools to aid researchers in both retrospective and prospective standardization of discrete entity types-such as disease names, cell types, or chemicals-that are used in metadata associated with biomedical data. W...

Annotating publicly-available samples and studies using interpretable modeling of unstructured metadata.

Briefings in bioinformatics
Reusing massive collections of publicly available biomedical data can significantly impact knowledge discovery. However, these public samples and studies are typically described using unstructured plain text, hindering the findability and further reu...

Automated annotation of scientific texts for ML-based keyphrase extraction and validation.

Database : the journal of biological databases and curation
Advanced omics technologies and facilities generate a wealth of valuable data daily; however, the data often lack the essential metadata required for researchers to find, curate, and search them effectively. The lack of metadata poses a significant c...

[A lightweight recurrence prediction model for high grade serous ovarian cancer based on hierarchical transformer fusion metadata].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi
High-grade serous ovarian cancer has a high degree of malignancy, and at detection, it is prone to infiltration of surrounding soft tissues, as well as metastasis to the peritoneum and lymph nodes, peritoneal seeding, and distant metastasis. Whether ...

Machine learning to predict notes for chart review in the oncology setting: a proof of concept strategy for improving clinician note-writing.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Leverage electronic health record (EHR) audit logs to develop a machine learning (ML) model that predicts which notes a clinician wants to review when seeing oncology patients.

pyM2aia: Python interface for mass spectrometry imaging with focus on deep learning.

Bioinformatics (Oxford, England)
SUMMARY: Python is the most commonly used language for deep learning (DL). Existing Python packages for mass spectrometry imaging (MSI) data are not optimized for DL tasks. We, therefore, introduce pyM2aia, a Python package for MSI data analysis with...