AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

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ImmuneData: an integrated data discovery system for immunology data repositories.

Database : the journal of biological databases and curation
UNLABELLED: To meet the increasing demand for data sharing, data reuse and meta-analysis in the immunology research community, we have developed the data discovery system ImmuneData. The system provides integrated access to five immunology data repos...

Musical Instrument Identification Using Deep Learning Approach.

Sensors (Basel, Switzerland)
The work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related t...

Understanding the Research Landscape of Deep Learning in Biomedical Science: Scientometric Analysis.

Journal of medical Internet research
BACKGROUND: Advances in biomedical research using deep learning techniques have generated a large volume of related literature. However, there is a lack of scientometric studies that provide a bird's-eye view of them. This absence has led to a partia...

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...

Rewritable two-dimensional DNA-based data storage with machine learning reconstruction.

Nature communications
DNA-based data storage platforms traditionally encode information only in the nucleotide sequence of the molecule. Here we report on a two-dimensional molecular data storage system that records information in both the sequence and the backbone struct...

Anatomy and the type concept in biology show that ontologies must be adapted to the diagnostic needs of research.

Journal of biomedical semantics
BACKGROUND: In times of exponential data growth in the life sciences, machine-supported approaches are becoming increasingly important and with them the need for FAIR (Findable, Accessible, Interoperable, Reusable) and eScience-compliant data and met...

Position of the AI for Health Imaging (AI4HI) network on metadata models for imaging biobanks.

European radiology experimental
A huge amount of imaging data is becoming available worldwide and an incredible range of possible improvements can be provided by artificial intelligence algorithms in clinical care for diagnosis and decision support. In this context, it has become e...

Ontology Development Kit: a toolkit for building, maintaining and standardizing biomedical ontologies.

Database : the journal of biological databases and curation
Similar to managing software packages, managing the ontology life cycle involves multiple complex workflows such as preparing releases, continuous quality control checking and dependency management. To manage these processes, a diverse set of tools i...

Systematic tissue annotations of genomics samples by modeling unstructured metadata.

Nature communications
There are currently >1.3 million human -omics samples that are publicly available. This valuable resource remains acutely underused because discovering particular samples from this ever-growing data collection remains a significant challenge. The maj...

Automated prediction of COVID-19 severity upon admission by chest X-ray images and clinical metadata aiming at accuracy and explainability.

Scientific reports
In the past few years COVID-19 posed a huge threat to healthcare systems around the world. One of the first waves of the pandemic hit Northern Italy severely resulting in high casualties and in the near breakdown of primary care. Due to these facts, ...