AIMC Topic: Metadata

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Assessment of the predictive potential of cognitive scores from retinal images and retinal fundus metadata via deep learning using the CLSA database.

Scientific reports
Accumulation of beta-amyloid in the brain and cognitive decline are considered hallmarks of Alzheimer's disease. Knowing from previous studies that these two factors can manifest in the retina, the aim was to investigate whether a deep learning metho...

The BMS-LM ontology for biomedical data reporting throughout the lifecycle of a research study: From data model to ontology.

Journal of biomedical informatics
Biomedical research data reuse and sharing is essential for fostering research progress. To this aim, data producers need to master data management and reporting through standard and rich metadata, as encouraged by open data initiatives such as the F...

Incorporating metadata in HIV transmission network reconstruction: A machine learning feasibility assessment.

PLoS computational biology
HIV molecular epidemiology estimates the transmission patterns from clustering genetically similar viruses. The process involves connecting genetically similar genotyped viral sequences in the network implying epidemiological transmissions. This tech...

An Attention-Based Mechanism to Combine Images and Metadata in Deep Learning Models Applied to Skin Cancer Classification.

IEEE journal of biomedical and health informatics
Computer-aided skin cancer classification systems built with deep neural networks usually yield predictions based only on images of skin lesions. Despite presenting promising results, it is possible to achieve higher performance by taking into accoun...

Predicting Age Groups of Reddit Users Based on Posting Behavior and Metadata: Classification Model Development and Validation.

JMIR public health and surveillance
BACKGROUND: Social media are important for monitoring perceptions of public health issues and for educating target audiences about health; however, limited information about the demographics of social media users makes it challenging to identify conv...

A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability.

The Lancet. Digital health
Health data that are publicly available are valuable resources for digital health research. Several public datasets containing ophthalmological imaging have been frequently used in machine learning research; however, the total number of datasets cont...

Jupyter notebook-based tools for building structured datasets from the Sequence Read Archive.

F1000Research
The Sequence Read Archive (SRA) is a large public repository that stores raw next-generation sequencing data from thousands of diverse scientific investigations.  Despite its promise, reuse and re-analysis of SRA data has been challenged by the heter...

Automation With Intelligence in Drug Research.

Clinical therapeutics
The industry has adopted Clinical Data Interchange Standards Consortium standards for clinical trial data and the Food and Drug Administration electronic common technical document standard for documents for many years but still faces many challenges....

Phenotype annotation with the ontology of microbial phenotypes (OMP).

Journal of biomedical semantics
BACKGROUND: Microbial genetics has formed a foundation for understanding many aspects of biology. Systematic annotation that supports computational data mining should reveal further insights for microbes, microbiomes, and conserved functions beyond m...