AIMC Topic: Europe
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Mathematical models and deep learning for predicting the number of individuals reported to be infected with SARS-CoV-2.
Journal of the Royal Society, Interface
Aug 5, 2020
We introduce a novel methodology for predicting the time evolution of the number of individuals in a given country reported to be infected with SARS-CoV-2. This methodology, which is based on the synergy of explicit mathematical formulae and deep lea...
The European artificial intelligence strategy: implications and challenges for digital health.
The Lancet. Digital health
Jun 23, 2020
In February, 2020, the European Commission published a white paper on artificial intelligence (AI) as well as an accompanying communication and report. The paper sets out policy options to facilitate a secure and trustworthy development of AI and con...
Predicting dengue importation into Europe, using machine learning and model-agnostic methods.
Scientific reports
Jun 16, 2020
The geographical spread of dengue is a global public health concern. This is largely mediated by the importation of dengue from endemic to non-endemic areas via the increasing connectivity of the global air transport network. The dynamic nature and i...
Looking for Mimicry in a Snake Assemblage Using Deep Learning.
The American naturalist
May 27, 2020
Batesian mimicry is a canonical example of evolution by natural selection, popularized by highly colorful species resembling unrelated models with astonishing precision. However, Batesian mimicry could also occur in inconspicuous species and rely on ...
Multiclass semantic segmentation and quantification of traumatic brain injury lesions on head CT using deep learning: an algorithm development and multicentre validation study.
The Lancet. Digital health
May 14, 2020
BACKGROUND: CT is the most common imaging modality in traumatic brain injury (TBI). However, its conventional use requires expert clinical interpretation and does not provide detailed quantitative outputs, which may have prognostic importance. We aim...
Implementation of eHealth and AI integrated diagnostics with multidisciplinary digitized data: are we ready from an international perspective?
European radiology
May 6, 2020
Digitization of medicine requires systematic handling of the increasing amount of health data to improve medical diagnosis. In this context, the integration of the versatile diagnostic information, e.g., from anamnesis, imaging, histopathology, and c...
Modelling the monthly abundance of Culicoides biting midges in nine European countries using Random Forests machine learning.
Parasites & vectors
Apr 15, 2020
BACKGROUND: Culicoides biting midges transmit viruses resulting in disease in ruminants and equids such as bluetongue, Schmallenberg disease and African horse sickness. In the past decades, these diseases have led to important economic losses for far...
PRIMAGE project: predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers.
European radiology experimental
Apr 3, 2020
PRIMAGE is one of the largest and more ambitious research projects dealing with medical imaging, artificial intelligence and cancer treatment in children. It is a 4-year European Commission-financed project that has 16 European partners in the consor...
Development of a system based on artificial intelligence to identify visual problems in children: study protocol of the TrackAI project.
BMJ open
Feb 17, 2020
INTRODUCTION: Around 70% to 80% of the 19 million visually disabled children in the world are due to a preventable or curable disease, if detected early enough. Vision screening in childhood is an evidence-based and cost-effective way to detect visua...
Automated body composition analysis of clinically acquired computed tomography scans using neural networks.
Clinical nutrition (Edinburgh, Scotland)
Jan 22, 2020
BACKGROUND & AIMS: The quantity and quality of skeletal muscle and adipose tissue is an important prognostic factor for clinical outcomes across several illnesses. Clinically acquired computed tomography (CT) scans are commonly used for quantificatio...
Automation
North America
Body Composition
Radiographic Image Interpretation, Computer-Assisted
Lumbar Vertebrae
Adiposity
Male
Middle Aged
Deep Learning
Europe
Female
Sarcopenia
Humans
Reproducibility of Results
Muscle, Skeletal
Neural Networks, Computer
Aged
Adipose Tissue
Tomography, X-Ray Computed
Adult
Predictive Value of Tests
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