Automated image contouring is showing improvements in efficiency for a number of clinical tasks in radiotherapy. While atlas segmentation has proven moderately beneficial, the next generation of algorithms based on convolutional neural networks is al...
BACKGROUND: Longitudinal measurement of glioma burden with MRI is the basis for treatment response assessment. In this study, we developed a deep learning algorithm that automatically segments abnormal fluid attenuated inversion recovery (FLAIR) hype...
The use of artificial intelligence (AI) in patient care can offer significant benefits. However, there is a lack of independent evaluation considering AI in use. The paper argues that consideration should be given to how AI will be incorporated into ...
Microfluidic devices have been increasingly used for low-volume liquid handling operations. However, laboratory automation of such delicate devices has lagged behind due to the lack of world-to-chip (macro-to-micro) interfaces. In this paper, we have...
Journal of the American Medical Informatics Association : JAMIA
Oct 1, 2019
OBJECTIVE: The objective of this study is to characterize the dynamic structure of primary care consultations by identifying typical activities and their inter-relationships to inform the design of automated approaches to clinical documentation using...
Tracing neurites constitutes the core of neuronal morphology reconstruction, a key step toward neuronal circuit mapping. Modern optical-imaging techniques allow observation of nearly complete mouse neuron morphologies across brain regions or even the...
Journal of the American College of Radiology : JACR
Sep 1, 2019
Recent advances in machine learning and artificial intelligence offer promising applications to radiology quality improvement initiatives as they relate to the radiology value network. Coordination within the interlocking web of systems, events, and ...
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