AIMC Topic: Germany

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Artificial intelligence in bone age assessment: accuracy and efficiency of a novel fully automated algorithm compared to the Greulich-Pyle method.

European radiology experimental
BACKGROUND: Bone age (BA) assessment performed by artificial intelligence (AI) is of growing interest due to improved accuracy, precision and time efficiency in daily routine. The aim of this study was to investigate the accuracy and efficiency of a ...

Machine Learning to Detect Alzheimer's Disease from Circulating Non-coding RNAs.

Genomics, proteomics & bioinformatics
Blood-borne small non-coding (sncRNAs) are among the prominent candidates for blood-based diagnostic tests. Often, high-throughput approaches are applied to discover biomarker signatures. These have to be validated in larger cohorts and evaluated by ...

Psychiatry and Fitness to Fly After Germanwings.

The journal of the American Academy of Psychiatry and the Law
In March 2015, a co-pilot flying Germanwings Flight 9525 deliberately pointed his airplane into a descent, killing himself, five other crew members, and 144 passengers. Subsequent investigation and review teams examined the incident and considered po...

Spatial-temporal variation characteristics and evolution of the global industrial robot trade: A complex network analysis.

PloS one
Industrial robots are a strategic future technology and an important part of the development of artificial intelligence, and they are a necessary means for the intelligent transformation of manufacturing industry. Based on global industrial robot tra...

Diagnosis and classification of pediatric acute appendicitis by artificial intelligence methods: An investigator-independent approach.

PloS one
Acute appendicitis is one of the major causes for emergency surgery in childhood and adolescence. Appendectomy is still the therapy of choice, but conservative strategies are increasingly being studied for uncomplicated inflammation. Diagnosis of acu...

Development and validation of the automated imaging differentiation in parkinsonism (AID-P): a multicentre machine learning study.

The Lancet. Digital health
BACKGROUND: Development of valid, non-invasive biomarkers for parkinsonian syndromes is crucially needed. We aimed to assess whether non-invasive diffusion-weighted MRI can distinguish between parkinsonian syndromes using an automated imaging approac...

Development and Validation of the Automated Imaging Differentiation in Parkinsonism (AID-P): A Multi-Site Machine Learning Study.

The Lancet. Digital health
BACKGROUND: There is a critical need to develop valid, non-invasive biomarkers for Parkinsonian syndromes. The current 17-site, international study assesses whether non-invasive diffusion MRI (dMRI) can distinguish between Parkinsonian syndromes.

Deep learning outperformed 136 of 157 dermatologists in a head-to-head dermoscopic melanoma image classification task.

European journal of cancer (Oxford, England : 1990)
BACKGROUND: Recent studies have successfully demonstrated the use of deep-learning algorithms for dermatologist-level classification of suspicious lesions by the use of excessive proprietary image databases and limited numbers of dermatologists. For ...