AIMC Topic: Automation

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CD-NuSS: A Web Server for the Automated Secondary Structural Characterization of the Nucleic Acids from Circular Dichroism Spectra Using Extreme Gradient Boosting Decision-Tree, Neural Network and Kohonen Algorithms.

Journal of molecular biology
Nucleic acids exhibit a repertoire of conformational preference depending on the sequence and environment. Circular dichroism (CD) is an essential and valuable tool for monitoring such secondary structural conformations of nucleic acids. Nonetheless,...

Machine learning-based automated classification of headache disorders using patient-reported questionnaires.

Scientific reports
Classification of headache disorders is dependent on a subjective self-report from patients and its interpretation by physicians. We aimed to apply objective data-driven machine learning approaches to analyze patient-reported symptoms and test the fe...

Automated quantification of myocardial tissue characteristics from native T mapping using neural networks with uncertainty-based quality-control.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Tissue characterisation with cardiovascular magnetic resonance (CMR) parametric mapping has the potential to detect and quantify both focal and diffuse alterations in myocardial structure not assessable by late gadolinium enhancement. Nat...

Complementary Deep and Shallow Learning with Boosting for Public Transportation Safety.

Sensors (Basel, Switzerland)
To monitor road safety, billions of records can be generated by Controller Area Network bus each day on public transportation. Automation to determine whether certain driving behaviour of drivers on public transportation can be considered safe on the...

Multi-to-binary network (MTBNet) for automated multi-organ segmentation on multi-sequence abdominal MRI images.

Physics in medicine and biology
Fully convolutional neural network (FCN) has achieved great success in semantic segmentation. However, the performance of the FCN is generally compromised for multi-object segmentation. Multi-organ segmentation is very common while challenging in the...

BMIVPOT, a Fully Automated Version of the Intravenous Pole: Simulation, Design, and Evaluation.

Journal of healthcare engineering
Robotic intravenous poles are automated supportive instrument that needs to be triggered by patients to hold medications and needed supplies. Healthcare engineering of robotic intravenous poles is advancing in order to improve the quality of health s...

Technical Note: Deep Learning approach for automatic detection and identification of patient positioning devices for radiation therapy.

Medical physics
PURPOSE: Automatic detection and identification of setup devices, using a deep convolutional neural network (CNN) for real-time multiclass object detection, has the potential to reduce errors in the treatment delivery process by avoiding documentatio...