Prior Authorization Delays Increase Patient Death Risk

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Source: Oncology Times - Category: Cancer & Oncology Tags: News Source Type: research

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Continuous human motion intent learning may be modeled using a Gaussian process (GP) autoregression based evolving system to cope with the unspecified and time-varying motion patterns. Electromyography (EMG) signals are the primary input. GP is used as a mathematical foundation to model human kinematics by adopting the nonlinear autoregressive with exogenous inputs (NARX) framework, and an evolving system is applied to learn the irregular and unspecified dynamic features. The statistical nature of the GP offers superior flexibility for learning human kinematics and is capable of giving credibility to motion intent predicti...
Source: IEEE Transactions on Biomedical Engineering - Category: Biomedical Engineering Source Type: research
Conclusion: This study confirmed that the soft prior algorithm is robust in 3-D and can function successfully across a range of complex geometries and tissue property distributions. Significance: This study demonstrates that our microwave tomography is capable of recovering accurate tissue property distributions when spatial information from MRI is incorporated through soft prior regularization.
Source: IEEE Transactions on Biomedical Engineering - Category: Biomedical Engineering Source Type: research
Conclusions: These results suggest that each simulator-type provided crucial information for evaluating surgical proficiency. The methods developed in this paper could improve evaluations of a surgeon's clinical proficiency as well as training potential in terms of basic- sensorimotor ability.
Source: IEEE Transactions on Biomedical Engineering - Category: Biomedical Engineering Source Type: research
Conclusion: We develop a novel approach for deconvolution of SC by employing the HMF method and capturing the significant spectral components of SC data. Significance: Recovering the underlying neural stimuli more accurately using this approach will potentially improve tracking emotional states in affective computing.
Source: IEEE Transactions on Biomedical Engineering - Category: Biomedical Engineering Source Type: research
Objective: The aim of the study was to show if pulse rise times (PRTs) extracted from photoplethysmographic (PPG) pulse waves (PWs) have an association with peripheral arterial disease (PAD) or its endovascular treatment, percutanoeus transluminal angioplasty (PTA) of the superficial femoral artery. Methods: Lower and upper limb PPG PWs were recorded and analyzed from 24 patients who suffered from PAD. The measurements were conducted before and after the treatment, and one month later by using transmission-mode PPG-probes placed in the index finger and second toe. Ankle-to-brachial pressure index and toe pressures were use...
Source: IEEE Transactions on Biomedical Engineering - Category: Biomedical Engineering Source Type: research
Conclusion: The proposed algorithm demonstrates superior reconstruction performance by delivering non-negative pixel values with no visible distortion of anatomical structures. Significance: Our method can enable quantitative optoacoustic imaging, and has the potential to improve preclinical and translational imaging applications.
Source: IEEE Transactions on Biomedical Engineering - Category: Biomedical Engineering Source Type: research
Objective: A new method for fitting diffusion-weighted magnetic resonance imaging (DW-MRI) data composed of an unknown number of multi-exponential components is presented and evaluated. Methods: The auto-regressive discrete acquisition points transformation (ADAPT) method is an adaption of the auto-regressive moving average system, which allows for the modeling of multi-exponential data and enables the estimation of the number of exponential components without prior assumptions. ADAPT was evaluated on simulated DW-MRI data. The optimum ADAPT fit was then applied to human brain DWI data and the correlation between the ADAPT...
Source: IEEE Transactions on Biomedical Engineering - Category: Biomedical Engineering Source Type: research
Conclusion: Radar micro-Doppler signatures and their Fourier transforms are well suited to capture changes in gait. Five different walking styles are recognized with high accuracy. Significance: Radar-based sensing of gait is an emerging technology with multi-faceted applications in security and health care industries. We show that radar, as a contact-less sensing technology, can supplement existing gait diagnostic tools with respect to long-term monitoring and reproducibility of the examinations.
Source: IEEE Transactions on Biomedical Engineering - Category: Biomedical Engineering Source Type: research
This study aims to extract a liver model from LDCT images for facilitating medical expert in surgical planning and post-operative assessment along with low radiation risk to the patient. Our method carried out liver extraction by employing residual convolutional neural networks (LER-CN), which is further refined by noise removal and structure preservation components. After patch-based training, our LER-CN shows a competitive performance relative to state-of-the-art methods for both clinical and publicly available MICCAI Sliver07 datasets. We have proposed training and learning algorithms for LER-CN based on back propagatio...
Source: IEEE Transactions on Biomedical Engineering - Category: Biomedical Engineering Source Type: research
In this study, we explore the use of low rank and sparse constraints for the noninvasive estimation of epicardial and endocardial extracellular potentials from body-surface electrocardiographic data to locate the focus of premature ventricular contractions (PVCs). The proposed strategy formulates the dynamic spatiotemporal distribution of cardiac potentials by means of low rank and sparse decomposition, where the low rank term represents the smooth background and the anomalous potentials are extracted in the sparse matrix. Compared to the most previous potential-based approaches, the proposed low rank and sparse constraint...
Source: IEEE Transactions on Biomedical Engineering - Category: Biomedical Engineering Source Type: research
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