AIMC Topic: Humans
Showing 66081 to 66090 of 95995 articles
Automatic 3D Bi-Ventricular Segmentation of Cardiac Images by a Shape-Refined Multi- Task Deep Learning Approach.
IEEE transactions on medical imaging
Jan 23, 2019
Deep learning approaches have achieved state-of-the-art performance in cardiac magnetic resonance (CMR) image segmentation. However, most approaches have focused on learning image intensity features for segmentation, whereas the incorporation of anat...
Lung and Pancreatic Tumor Characterization in the Deep Learning Era: Novel Supervised and Unsupervised Learning Approaches.
IEEE transactions on medical imaging
Jan 23, 2019
Risk stratification (characterization) of tumors from radiology images can be more accurate and faster with computer-aided diagnosis (CAD) tools. Tumor characterization through such tools can also enable non-invasive cancer staging, prognosis, and fo...
Deep Learning: Current and Emerging Applications in Medicine and Technology.
IEEE journal of biomedical and health informatics
Jan 23, 2019
Machine learning is enabling researchers to analyze and understand increasingly complex physical and biological phenomena in traditional fields such as biology, medicine, and engineering and emerging fields like synthetic biology, automated chemical ...
Improving Prediction Performance Using Hierarchical Analysis of Real-Time Data: A Sepsis Case Study.
IEEE journal of biomedical and health informatics
Jan 23, 2019
This paper presents a novel method for hierarchical analysis of machine learning algorithms to improve predictions of at risk patients, thus further enabling prompt therapy. Specifically, we develop a multi-layer machine learning approach to analyze ...
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Predicting radiation pneumonitis in locally advanced stage II-III non-small cell lung cancer using machine learning.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Jan 23, 2019
BACKGROUND AND PURPOSE: Radiation pneumonitis (RP) is a radiotherapy dose-limiting toxicity for locally advanced non-small cell lung cancer (LA-NSCLC). Prior studies have proposed relevant dosimetric constraints to limit this toxicity. Using machine ...
A Computational Framework for Genome-wide Characterization of the Human Disease Landscape.
Cell systems
Jan 23, 2019
A key challenge for the diagnosis and treatment of complex human diseases is identifying their molecular basis. Here, we developed a unified computational framework, URSA (Unveiling RNA Sample Annotation for Human Diseases), that leverages machine le...
Physical characteristics not psychological state or trait characteristics predict motion during resting state fMRI.
Scientific reports
Jan 23, 2019
Head motion (HM) during fMRI acquisition can significantly affect measures of brain activity or connectivity even after correction with preprocessing methods. Moreover, any systematic relationship between HM and variables of interest can introduce sy...
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KeratoDetect: Keratoconus Detection Algorithm Using Convolutional Neural Networks.
Computational intelligence and neuroscience
Jan 23, 2019
Keratoconus (KTC) is a noninflammatory disorder characterized by progressive thinning, corneal deformation, and scarring of the cornea. The pathological mechanisms of this condition have been investigated for a long time. In recent years, this diseas...
Robotic hand illusion with tactile feedback: Unravelling the relative contribution of visuotactile and visuomotor input to the representation of body parts in space.
PloS one
Jan 23, 2019
The rubber hand illusion describes a phenomenon in which participants experience a rubber hand as being part of their body by the synchronous application of visuotactile stimulation to the real and the artificial limb. In the recently introduced robo...
Models Matter, So Does Training: An Empirical Study of CNNs for Optical Flow Estimation.
IEEE transactions on pattern analysis and machine intelligence
Jan 22, 2019
We investigate two crucial and closely-related aspects of CNNs for optical flow estimation: models and training. First, we design a compact but effective CNN model, called PWC-Net, according to simple and well-established principles: pyramidal proces...
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