AIMC Topic: Data Management

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The PACIFIC ontology for heterogeneous data management in cardiology.

Journal of biomedical informatics
With the emergence of health data warehouses and major initiatives to collect and analyze multi-modal and multisource data, data organization becomes central. In the PACIFIC-PRESERVED (PhenomApping, ClassIFication, and Innovation for Cardiac Dysfunct...

A knowledge graph-based data harmonization framework for secondary data reuse.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The adoption of new technologies in clinical care systems has propitiated the availability of a great amount of valuable data. However, this data is usually heterogeneous, requiring its harmonization to be integrated and ana...

Spatial attention-based residual network for human burn identification and classification.

Scientific reports
Diagnosing burns in humans has become critical, as early identification can save lives. The manual process of burn diagnosis is time-consuming and complex, even for experienced doctors. Machine learning (ML) and deep convolutional neural network (CNN...

Drug repurposing: Known knowns to unknown unknowns - Network analysis of the repurposome.

Drug discovery today
DrugRepurposing Online is a database of well-curated literature examples of drug repurposing, structured by reference to compounds and indications, via a generalisation layer (within specific datasets) of mechanism. References are categorised by leve...

Recommendations to overcome barriers to the use of artificial intelligence-driven evidence in health technology assessment.

Frontiers in public health
BACKGROUND: Artificial intelligence (AI) has attracted much attention because of its enormous potential in healthcare, but uptake has been slow. There are substantial barriers that challenge health technology assessment (HTA) professionals to use AI-...

Conceptual framework and documentation standards of cystoscopic media content for artificial intelligence.

Journal of biomedical informatics
BACKGROUND: The clinical documentation of cystoscopy includes visual and textual materials. However, the secondary use of visual cystoscopic data for educational and research purposes remains limited due to inefficient data management in routine clin...

Ethics and governance of trustworthy medical artificial intelligence.

BMC medical informatics and decision making
BACKGROUND: The growing application of artificial intelligence (AI) in healthcare has brought technological breakthroughs to traditional diagnosis and treatment, but it is accompanied by many risks and challenges. These adverse effects are also seen ...

Global output on artificial intelligence in the field of nursing: A bibliometric analysis and science mapping.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing
PURPOSE: To analyze the AI research in the field of nursing, to explore the current situation, hot topics, and prospects of AI research in the field of nursing, and to provide a reference for researchers to carry out related studies.

microbeSEG: A deep learning software tool with OMERO data management for efficient and accurate cell segmentation.

PloS one
In biotechnology, cell growth is one of the most important properties for the characterization and optimization of microbial cultures. Novel live-cell imaging methods are leading to an ever better understanding of cell cultures and their development....

Unsupervised SAR Imagery Feature Learning with Median Filter-Based Loss Value.

Sensors (Basel, Switzerland)
The scarcity of open SAR (Synthetic Aperture Radars) imagery databases (especially the labeled ones) and sparsity of pre-trained neural networks lead to the need for heavy data generation, augmentation, or transfer learning usage. This paper describe...