AIMC Topic: Adolescent

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A multi-scale data fusion framework for bone age assessment with convolutional neural networks.

Computers in biology and medicine
Bone age assessment (BAA) has various clinical applications such as diagnosis of endocrine disorders and prediction of final adult height for adolescents. Recent studies indicate that deep learning techniques have great potential in developing automa...

Predicting Ewing Sarcoma Treatment Outcome Using Infrared Spectroscopy and Machine Learning.

Molecules (Basel, Switzerland)
BACKGROUND: Improved outcome prediction is vital for the delivery of risk-adjusted, appropriate and effective care to paediatric patients with Ewing sarcoma-the second most common paediatric malignant bone tumour. Fourier transform infrared (FTIR) sp...

A scalable machine learning approach for measuring violent and peaceful forms of political protest participation with social media data.

PloS one
In this paper, we introduce a scalable machine learning approach accompanied by open-source software for identifying violent and peaceful forms of political protest participation using social media data. While violent political protests are statistic...

MTBI Identification From Diffusion MR Images Using Bag of Adversarial Visual Features.

IEEE transactions on medical imaging
In this paper, we propose bag of adversarial features (BAFs) for identifying mild traumatic brain injury (MTBI) patients from their diffusion magnetic resonance images (MRIs) (obtained within one month of injury) by incorporating unsupervised feature...

3D radiotherapy dose prediction on head and neck cancer patients with a hierarchically densely connected U-net deep learning architecture.

Physics in medicine and biology
The treatment planning process for patients with head and neck (H&N) cancer is regarded as one of the most complicated due to large target volume, multiple prescription dose levels, and many radiation-sensitive critical structures near the target. Tr...

Self-Anamnesis with a Conversational User Interface: Concept and Usability Study.

Methods of information in medicine
OBJECTIVE: Self-anamnesis is a procedure in which a patient answers questions about the personal medical history without interacting directly with a doctor or medical assistant. If collected digitally, the anamnesis data can be shared among the healt...

Deep Collaborative Learning With Application to the Study of Multimodal Brain Development.

IEEE transactions on bio-medical engineering
OBJECTIVE: Multi-modal functional magnetic resonance imaging has been widely used for brain research. Conventional data-fusion methods cannot capture complex relationship (e.g., nonlinear predictive relationship) between multiple data. This paper aim...

Development of an intelligent decision support system for ischemic stroke risk assessment in a population-based electronic health record database.

PloS one
BACKGROUND: Intelligent decision support systems (IDSS) have been applied to tasks of disease management. Deep neural networks (DNNs) are artificial intelligent techniques to achieve high modeling power. The application of DNNs to large-scale data fo...

Machine learning identifies an immunological pattern associated with multiple juvenile idiopathic arthritis subtypes.

Annals of the rheumatic diseases
OBJECTIVES: Juvenile idiopathic arthritis (JIA) is the most common class of childhood rheumatic diseases, with distinct disease subsets that may have diverging pathophysiological origins. Both adaptive and innate immune processes have been proposed a...