AIMC Topic: Humans
Showing 66911 to 66920 of 95995 articles
A machine-learning approach to volitional control of a closed-loop deep brain stimulation system.
Journal of neural engineering
Nov 16, 2018
OBJECTIVE: Deep brain stimulation (DBS) is a well-established treatment for essential tremor, but may not be an optimal therapy, as it is always on, regardless of symptoms. A closed-loop (CL) DBS, which uses a biosignal to determine when stimulation ...
A deep neural network learning algorithm outperforms a conventional algorithm for emergency department electrocardiogram interpretation.
Journal of electrocardiology
Nov 16, 2018
BACKGROUND: Cardiologs® has developed the first electrocardiogram (ECG) algorithm that uses a deep neural network (DNN) for full 12‑lead ECG analysis, including rhythm, QRS and ST-T-U waves. We compared the accuracy of the first version of Cardiologs...
Domain-specific classification-pretrained fully convolutional network encoders for skin lesion segmentation.
Computers in biology and medicine
Nov 16, 2018
BACKGROUND AND OBJECTIVE: Fully convolutional neural networks have been shown to perform well for automated skin lesion segmentation on digital dermatoscopic images. Our concept is that transferring encoder weights from a network trained on a classif...
The European Federation of Organisations for Medical Physics (EFOMP) White Paper: Big data and deep learning in medical imaging and in relation to medical physics profession.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Nov 16, 2018
Big data and deep learning will profoundly change various areas of professions and research in the future. This will also happen in medicine and medical imaging in particular. As medical physicists, we should pursue beyond the concept of technical qu...
Preliminary study on alginate/NIPAM hydrogel-based soft microrobot for controlled drug delivery using electromagnetic actuation and near-infrared stimulus.
Biomedical microdevices
Nov 16, 2018
Currently, microrobots are receiving attention because of their small size and motility, which can be applied to minimal invasive therapy. Additionally, various microrobots using hydrogel with the characteristics of biocompatibility and biodegradabil...
In vitro neural networks minimise variational free energy.
Scientific reports
Nov 16, 2018
In this work, we address the neuronal encoding problem from a Bayesian perspective. Specifically, we ask whether neuronal responses in an in vitro neuronal network are consistent with ideal Bayesian observer responses under the free energy principle....
Ossification area localization in pediatric hand radiographs using deep neural networks for object detection.
PloS one
Nov 16, 2018
BACKGROUND: Detection of ossification areas of hand bones in X-ray images is an important task, e.g. as a preprocessing step in automated bone age estimation. Deep neural networks have emerged recently as de facto standard detection methods, but thei...
Robot-assisted percutaneous placement of K-wires during minimally invasive interventions of the spine.
Minimally invasive therapy & allied technologies : MITAT : official journal of the Society for Minimally Invasive Therapy
Nov 15, 2018
To assess the accuracy and time requirements of image-guided percutaneous K-wire insertion in the spine using an advanced robot assistance device for needle guidance and to demonstrate a radiation-free workflow for the physician. A planning CT-scan...
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Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging.
European radiology
Nov 15, 2018
OBJECTIVES: Preoperative, noninvasive prediction of the meningioma grade is important because it influences the treatment strategy. The purpose of this study was to evaluate the role of radiomics features of postcontrast T1-weighted images (T1C), app...
Social Conformity Effects on Trust in Simulation-Based Human-Robot Interaction.
Human factors
Nov 15, 2018
OBJECTIVE: We investigated the co-acting influences of communication and social conformity on trust in human-robot interaction.
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