AIMC Topic:
Data Mining

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Combining Literature Mining and Machine Learning for Predicting Biomedical Discoveries.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2022
The major outcomes and insights of scientific research and clinical study end up in the form of publication or clinical record in an unstructured text format. Due to advancements in biomedical research, the growth of published literature is getting t...
Drug Repositioning Biomedical Research Data Mining Machine Learning
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Biomedical Literature Mining for Repurposing Laboratory Tests.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2022
Epidemiological studies identifying biological markers of disease state are valuable, but can be time-consuming, expensive, and require extensive intuition and expertise. Furthermore, not all hypothesized markers will be borne out in a study, suggest...
Data Mining Publications Electronic Health Records Models, Statistical Machine Learning
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Application of Artificial Intelligence in Drug Discovery.

Current pharmaceutical design Jan 1, 2022
Due to the heap of data sets available for drug discovery, modern drug discovery has taken the shape of big data. Usage of Artificial intelligence (AI) can help to modify drug discovery based on big data to precised, knowledgeable data. The pharmaceu...
Artificial Intelligence Humans Data Mining Big Data Drug Development Drug Discovery
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A Practical Guide to Integrating Multimodal Machine Learning and Metabolic Modeling.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2022
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...
Data Mining Genome Systems Biology Humans Neoplasms Machine Learning
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Deep Mining from Omics Data.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2022
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...
Data Mining Neural Networks, Computer Support Vector Machine Machine Learning
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Pre- and Post-publication Verification for Reproducible Data Mining in Macromolecular Crystallography.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2022
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...
Humans Artificial Intelligence Data Mining Macromolecular Substances SARS-CoV-2 COVID-19 Synchrotrons Crystallography Crystallography, X-Ray
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Machine learning on small size samples: A synthetic knowledge synthesis.

Science progress Jan 1, 2022
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...
International Cooperation Data Mining Big Data Machine Learning Bibliometrics United States
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A Keyword Approach to Identify Adverse Events Within Narrative Documents From 4 Italian Institutions.

Journal of patient safety Jan 1, 2022
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...
Humans Natural Language Processing Data Mining Postoperative Complications Electronic Health Records
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Natural Language Processing of Nursing Notes: A Systematic Review.

Studies in health technology and informatics Dec 15, 2021
Natural Language Processing Electronic Health Records Data Mining
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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 Dec 1, 2021
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...
Natural Language Processing Data Mining Patient Safety Algorithms Machine Learning Humans
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