From mid-March through May 2020, New York City was the world's epicenter of the COVID-19 pandemic, and its hospitals faced an unparalleled surge of patients who were critically ill with the virus. In addition to putting an enormous strain on medical resources, the pandemic presented many ethical issues to emotionally and physically stressed clinicians and hospital administrators. Analyses of the challenges faced by the ethics consultation services of the two campuses of New York Presbyterian Hospital, and how they assisted their clinician and administrative colleagues, is the subject of the following four articles.The objective of this study is to determine X-ray dose distribution and the correlation between central, peripheral and weighted-centre peripheral doses for various phantom sizes and tube voltages in computed tomography (CT). We used phantoms developed in-house, with various water-equivalent diameters (Dw) from 8.5 up to 42.1 cm. The phantoms have one hole in the centre and four holes at the periphery. By using these five holes, it is possible to measure the size-specific central dose (Ds,c), peripheral dose (Ds,p), and weighted dose (Ds,w).The phantoms are scanned using a CT scanner (Siemens Somatom Definition AS), with the tube voltage varied from 80 up to 140 kVps. The doses are measured using a pencil ionization chamber (Ray safe X2 CT Sensor) in every hole for all phantoms. The relationships between Ds,c, Ds,p, and Ds,w, and the water-equivalent diameter are established. The size-conversion factors are calculated. Comparisons between Ds,c, Ds,p, and Ds,ware also established. We observe that the dose is relatively homogeneous over the phantom for water-equivalent diameters of 12-14 cm. For water-equivalent diameters less than 12 cm, the dose in the centre is higher than at the periphery, whereas for water-equivalent diameters greater than 14 cm, the dose at the centre is lower than that at the periphery. selleck We also find that the distribution of the doses is influenced by the tube voltage. These dose distributions may be useful for calculating organ doses for specific patients using their CT images in future clinical practice.
The novel coronavirus disease 2019 (COVID-19) constitutes a public health emergency globally. The number of infected people and deaths are proliferating every day, which is putting tremendous pressure on our social and healthcare system. Rapid detection of COVID-19 cases is a significant step to fight against this virus as well as release pressure off the healthcare system.
One of the critical factors behind the rapid spread of COVID-19 pandemic is a lengthy clinical testing time. The imaging tool, such as Chest X-ray (CXR), can speed up the identification process. Therefore, our objective is to develop an automated CAD system for the detection of COVID-19 samples from healthy and pneumonia cases using CXR images.
Due to the scarcity of the COVID-19 benchmark dataset, we have employed deep transfer learning techniques, where we examined 15 different pre-trained CNN models to find the most suitable one for this task.
A total of 860 images (260 COVID-19 cases, 300 healthy and 300 pneumonia cases) have been employed to investigate the performance of the proposed algorithm, where 70% images of each class are accepted for training, 15% is used for validation, and rest is for testing. It is observed that the VGG19 obtains the highest classification accuracy of 89.3% with an average precision, recall, and F1 score of 0.90, 0.89, 0.90, respectively.
This study demonstrates the effectiveness of deep transfer learning techniques for the identification of COVID-19 cases using CXR images.
This study demonstrates the effectiveness of deep transfer learning techniques for the identification of COVID-19 cases using CXR images.
The control of clinical manifestation of vestibular system relies on an optimal diagnosis. This study aims to develop and test a new automated diagnostic scheme for vestibular disorder recognition.
In this study we stratify the Ellipse-fitting technique using the Video Nysta Gmographic (VNG) sequence to obtain the segmented pupil region. Furthermore, the proposed methodology enabled us to select the most optimum VNG features to effectively conduct quantitative evaluation of nystagmus signal. The proposed scheme using a multilayer neural network classifier (MNN) was tested using a dataset involving 98 patients affected by VD and 41 normal subjects.
The new MNN scheme uses only five temporal and frequency parameters selected out of initial thirteen parameters. The scheme generated results reached 94% of classification accuracy.
The developed expert system is promising in solving the problem of VNG analysis and achieving accurate results of vestibular disorder recognition or diagnosis comparing to other methods or classifiers.
The developed expert system is promising in solving the problem of VNG analysis and achieving accurate results of vestibular disorder recognition or diagnosis comparing to other methods or classifiers.
The supplementary motor area (SMA) is implicated in both motor initiation and stereotypic multi-limb movements such as walking with arm swing. Gait in Parkinson's disease exhibits starting difficulties and reduced arm swing, consistent with reduced SMA activity.
We tested whether enhanced arm swing could improve Parkinson gait initiation and assessed whether increased SMA activity during preparation might facilitate such improvement.
Effects of instructed arm swing on cortical activity, muscle activity and kinematics were assessed by ambulant EEG, EMG, accelerometers and video in 17 Parkinson patients and 19 controls. At baseline, all participants repeatedly started walking after a simple auditory cue. Next, patients started walking at this cue, which now meant starting with enhanced arm swing. EEG changes over the putative SMA and leg motor cortex were assessed by event related spectral perturbation (ERSP) analysis of recordings at Fz and Cz.
Over the putative SMA location (Fz), natural PD gait initiation showed enhanced alpha/theta synchronization around the auditory cue, and reduced alpha/beta desynchronization during gait preparation and movement onset, compared to controls. Leg muscle activity in patients was reduced during preparation and movement onset, while the latter was delayed compared to controls. When starting with enhanced arm swing, these group differences virtually disappeared.
Instructed arm swing improves Parkinson gait initiation. ERSP normalization around the cue indicates that the attributed information may serve as a semi-internal cue, recruiting an internalized motor program to overcome initiation difficulties.
Instructed arm swing improves Parkinson gait initiation. ERSP normalization around the cue indicates that the attributed information may serve as a semi-internal cue, recruiting an internalized motor program to overcome initiation difficulties.selleck
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