AIMC Topic: Data Mining

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A Practical Guide to Integrating Multimodal Machine Learning and Metabolic Modeling.

Methods in molecular biology (Clifton, N.J.)
Complex, distributed, and dynamic sets of clinical biomedical data are collectively referred to as multimodal clinical data. In order to accommodate the volume and heterogeneity of such diverse data types and aid in their interpretation when they are...

Deep Mining from Omics Data.

Methods in molecular biology (Clifton, N.J.)
Since the advent of high-throughput omics technologies, various molecular data such as genes, transcripts, proteins, and metabolites have been made widely available to researchers. This has afforded clinicians, bioinformaticians, statisticians, and d...

Pre- and Post-publication Verification for Reproducible Data Mining in Macromolecular Crystallography.

Methods in molecular biology (Clifton, N.J.)
Like an article narrative is deemed by an editor and referees to be worthy of being a version of record on acceptance as a publication, so must the underpinning data also be scrutinized before passing it as a version of record. Indeed without the und...

Machine learning on small size samples: A synthetic knowledge synthesis.

Science progress
Machine Learning is an increasingly important technology dealing with the growing complexity of the digitalised world. Despite the fact, that we live in a 'Big data' world where, almost 'everything' is digitally stored, there are many real-world situ...

A Keyword Approach to Identify Adverse Events Within Narrative Documents From 4 Italian Institutions.

Journal of patient safety
OBJECTIVES: Existing methods for measuring adverse events in hospitals intercept a restricted number of events. Text mining refers to a range of techniques to extract data from narrative sources. The goal of this study was to evaluate the performance...

Realizing the Power of Text Mining and Natural Language Processing for Analyzing Patient Safety Event Narratives: The Challenges and Path Forward.

Journal of patient safety
Patient safety event (PSE) reports are a useful lens to understand hazards and patient safety risks in healthcare systems. However, patient safety officers and analysts in healthcare systems and safety organizations are challenged to make sense of th...

Deep learning methods for biomedical named entity recognition: a survey and qualitative comparison.

Briefings in bioinformatics
The biomedical literature is growing rapidly, and the extraction of meaningful information from the large amount of literature is increasingly important. Biomedical named entity (BioNE) identification is one of the critical and fundamental tasks in b...

A neuro-symbolic method for understanding free-text medical evidence.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We introduce Medical evidence Dependency (MD)-informed attention, a novel neuro-symbolic model for understanding free-text clinical trial publications with generalizability and interpretability.

PharmKG: a dedicated knowledge graph benchmark for bomedical data mining.

Briefings in bioinformatics
Biomedical knowledge graphs (KGs), which can help with the understanding of complex biological systems and pathologies, have begun to play a critical role in medical practice and research. However, challenges remain in their embedding and use due to ...