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Risk Analysis of Earth-Rock Dam Failures Based on Fuzzy Event Tree Method.

International journal of environmental research and public health
Earth-rock dams make up a large proportion of the dams in China, and their failures can induce great risks. In this paper, the risks associated with earth-rock dam failure are analyzed from two aspects: the probability of a dam failure and the result...

Pulmonary Nodule Recognition Based on Multiple Kernel Learning Support Vector Machine-PSO.

Computational and mathematical methods in medicine
Pulmonary nodule recognition is the core module of lung CAD. The Support Vector Machine (SVM) algorithm has been widely used in pulmonary nodule recognition, and the algorithm of Multiple Kernel Learning Support Vector Machine (MKL-SVM) has achieved ...

Small lung nodules detection based on local variance analysis and probabilistic neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: In medical examinations doctors use various techniques in order to provide to the patients an accurate analysis of their actual state of health. One of the commonly used methodologies is the x-ray screening. This examination...
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Building predictive in vitro pulmonary toxicity assays using high-throughput imaging and artificial intelligence.

Archives of toxicology
Human lungs are susceptible to the toxicity induced by soluble xenobiotics. However, the direct cellular effects of many pulmonotoxic chemicals are not always clear, and thus, a general in vitro assay for testing pulmonotoxicity applicable to a wide ...

High-precision quality assurance of robotic couches with six degrees of freedom.

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)
A robotic couch capable of six degrees of freedom (6-DoF) of motion was introduced for state-of-the-art radiation therapy. Patient treatment requires precise quality assurance (QA) of 6-DoF. Unfortunately, conventional methods do not provide the requ...

Muscleless motor synergies and actions without movements: From motor neuroscience to cognitive robotics.

Physics of life reviews
Emerging trends in neurosciences are providing converging evidence that cortical networks in predominantly motor areas are activated in several contexts related to 'action' that do not cause any overt movement. Indeed for any complex body, human or e...

Multi-task prediction of infant cognitive scores from longitudinal incomplete neuroimaging data.

NeuroImage
Early postnatal brain undergoes a stunning period of development. Over the past few years, research on dynamic infant brain development has received increased attention, exhibiting how important the early stages of a child's life are in terms of brai...

Automated classification of celiac disease during upper endoscopy: Status quo and quo vadis.

Computers in biology and medicine
A large amount of digital image material is routinely captured during esophagogastroduodenoscopies but, for the most part, is not used for confirming the diagnosis process of celiac disease which is primarily based on histological examination of biop...
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Deep D-Bar: Real-Time Electrical Impedance Tomography Imaging With Deep Neural Networks.

IEEE transactions on medical imaging
The mathematical problem for electrical impedance tomography (EIT) is a highly nonlinear ill-posed inverse problem requiring carefully designed reconstruction procedures to ensure reliable image generation. D-bar methods are based on a rigorous mathe...

Transferring and generalizing deep-learning-based neural encoding models across subjects.

NeuroImage
Recent studies have shown the value of using deep learning models for mapping and characterizing how the brain represents and organizes information for natural vision. However, modeling the relationship between deep learning models and the brain (or ...
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