LLukas22/scidocs huggingface dataset:
Planning for Action: The Impact of an Asthma Action Plan Decision Support Tool Integrated into an Electronic Health Record (EHR) at a Large Health Care System.

INTRODUCTION
Asthma is a chronic airway disease that can be difficult to manage, resulting in poor outcomes and high costs. Asthma action plans assist patients with self-management, but provider compliance with this recommendation is limited in part because of guideline complexity. This project aimed to embed an electronic asthma action plan decision support tool (eAAP) into the medical record to streamline evidence-based guidelines for providers at the point of care, create individualized patient handouts, and evaluate effects on disease outcomes.


METHODS
eAAP development occurred in 4 phases: web-based prototype creation, multidisciplinary team engagement, pilot, and system-wide dissemination. Medical record and hospital billing data compared frequencies of asthma exacerbations before and after eAAP receipt with matched controls.


RESULTS
Between December 2012 and September 2014, 5174 patients with asthma (∼10%) received eAAPs. Results showed an association between eAAP receipt and significant reductions in pediatric asthma exacerbations, including 33% lower odds of requiring oral steroids (P < .001), compared with controls. Equivalent adult measures were not statistically significant.


CONCLUSIONS
This study supports existing evidence that patient self-management plays an important role in reducing asthma exacerbations. We show the feasibility of leveraging technology to provide guideline-based decision support through an eAAP, addressing known challenges of implementation into routine practice.
An Improved Harris-Affine Invariant Interest Point Detector

Interest point detection is essential process for many computer vision applications, which must provide invariant points to several image variations, such as, rotation, zoom, blur, illumination variation and change of viewpoints. Harris-Affine detector is considered as one of the most effective interest point detectors, although it still presents vulnerability to some image. This paper proposes an improved Harris-affine interest point detector based on two-dimensional weight Atomic functions to improve the repeatability and stability of detected points of Harris-Affine detector, in which the Gaussian kernel is replaced by the ) (x up Atomic Function. Evaluation results show that the new image interest point detector, called Atomic Harris-Affine detector, improves the repeatability in about 40% compared with the conventional Harris-Affine detector, under several conditions such as blurring, illumination changes, change of viewpoint, as well as other geometrical and affine transformations. Key-Words: interest points detector; Atomic function; Harris-Affine detector; repeatability; convergence rate
Effect of granulocyte-macrophage colony-stimulating factor on oral mucositis in head and neck cancer patients after cisplatin, fluorouracil, and leucovorin chemotherapy.

PURPOSE
To evaluate prospectively the efficacy of granulocyte-macrophage colony-stimulating factor (GM-CSF) in the reduction of chemotherapy-induced oral mucositis.


PATIENTS AND METHODS
Twenty patients with stage IV squamous cell carcinoma of head and neck were studied. Two-cycles (periods) of identical doses of cisplatin, fluorouracil (5-FU), and leucovorin (PFL) chemotherapy with cisplatin 20 mg/m2/d, 5-FU 800 mg/m2/d, leucovorin 90 mg/m2/d by 96-hour continuous intravenous infusion every 3 weeks were given to each patient. After PFL chemotherapy, GM-CSF 4 micrograms/kg subcutaneously from days 5 to 14 or no therapy was given by a randomized self-controlled crossover study design. Oral mucositis was graded with modified Radiation Therapy Oncology Group criteria.


RESULTS
In the first cycle of PFL chemotherapy, GM-CSF significantly reduced the incidence, mean duration, and mean area under the curve (AUC) of severe oral gross mucositis (grade > or = 3) compared with no therapy. These beneficial effects continued into the second cycle of PFL chemotherapy after crossover to no GM-CSF. The incidence of severe mucositis was reduced when GM-CSF was given in the second cycle of PFL. Analysis of variance indicated significant direct GM-CSF treatment effects on the mean AUC of gross/functional scores and duration of moderate gross mucositis (grade > or = 2) over both periods. There was a significant period effect in favor of giving GM-CSF in the first cycle of chemotherapy.


CONCLUSION
GM-CSF can significantly reduce the severity and duration of chemotherapy-induced oral mucositis after PFL chemotherapy.
International consensus recommendations on the aesthetic usage of botulinum toxin type A (Speywood Unit)--Part II: Wrinkles on the middle and lower face, neck and chest.

BACKGROUND
Azzalure® (Galderma SA), a newly approved European botulinum neurotoxin type A (BoNT-A), is derived from Dysport™ (Ipsen Ltd.), which has a 20-year history of product consistency and has been widely used for various aesthetic and therapeutic applications. Azzalure® and Dysport™ are collectively referred to as BoNT-A (Speywood Unit) after the unit of their activity, and are distinct from other commercial BoNT-A preparations. Consensus has been developed for the treatment of upper facial wrinkles with BoNT-A (Speywood Unit).


OBJECTIVE
To provide consensus recommendations on the treatment with BoNT-A (Speywood Unit) for wrinkles on the middle and lower face, neck and chest region.


METHODS
The members of the International Board on Botulinum toxin Azzalure (IBBA) convened to develop consensus based on their extensive experience.


RESULTS
The recommended final concentration of BoNT-A (Speywood Unit) is 200 Speywood Units/ml after reconstitution. The consensus recommendations were provided for nine indications, including lower eyelid wrinkles, bunny lines, drooping nasal tip, perioral wrinkles, masseter hypertrophy, drooping mouth corners, dimpled chin, platysmal bands and décolleté wrinkles. For each indication, anatomy of the region to be treated was discussed, as were potential side-effects. The consensus recommendations included the number and location of the injection points, dose range of each point and the total injection, as well as specific injection technique.


CONCLUSION
These recommendations provide a guideline for physicians who wish to perform safe and efficacious treatment with BoNT-A (Speywood Unit) on the less commonly treated middle and lower face, neck and chest region.
High-degree cubature Kalman filter

The cubature Kalman filter (CKF), which is based on the third degree spherical–radial cubature rule, is numericallymore stable than the unscented Kalman filter (UKF) but less accurate than theGauss–Hermite quadrature filter (GHQF). To improve the performance of the CKF, a new class of CKFs with arbitrary degrees of accuracy in computing the spherical and radial integrals is proposed. The third-degree CKF is a special case of the class. The high-degree CKFs of the class can achieve the accuracy and stability performances close to those of the GHQF but at lower computational cost. A numerical integration problem and a target tracking problem are utilized to demonstrate the necessity of using the high-degree cubature rules to improve the performance. The target tracking simulation shows that the fifth-degree CKF can achieve higher accuracy than the extended Kalman filter, the UKF, the third-degree CKF, and the particle filter, and is computationally much more efficient than the GHQF. © 2012 Elsevier Ltd. All rights reserved.
Eye detection for a real-time vehicle driver fatigue monitoring system

With the vast amount of vehicles on roads worldwide on any given time of day, the severity of fatigue related accidents have become a major concern. The obvious solution to prevent or at least decrease fatigue related accidents, is to ensure that the driver rests frequently. However, the simple fact of the matter is that frequent resting periods cannot be effectively enforced, and as a result there is a need for a system to monitor the level of driver fatigue in real-time. The ultimate goal of this research is to develop a camera-based driver fatigue monitoring system, centered around the tracking of driver's eyes, since the eyes provide the most information with regards to fatigue. The most critical aspect of eye tracking is to first accurately detect the eyes, and although a number of eye trackers have already been illustrated in the literature, the process of eye detection has seldom been described in much detail. Given a number of possible eye candidate sub-images, eye detection is in essence the classification of these sub-images as either eyes or non-eyes. To the knowledge of the authors, different classification techniques have not been directly compared for the purpose of eye detection, and therefore the aim of this paper is to evaluate different classification techniques to determine which technique will be the most suitable for a driver fatigue monitoring system. The classification techniques that have been considered are artificial neural networks (ANN), support vector machines (SVM) and adaptive boosting (AdaBoost). Results have shown that AdaBoost will be the most suitable eye classification technique for a real-world driver fatigue monitoring system.
A JPEG backward-compatible HDR image compression

High Dynamic Range (HDR) imaging is expected to become one of the technologies that could shape next generation of consumer digital photography. Manufacturers are rolling out cameras and displays capable of capturing and rendering HDR images. The popularity and full public adoption of HDR content is however hindered by the lack of standards in evaluation of quality, file formats, and compression, as well as large legacy base of Low Dynamic Range (LDR) displays that are unable to render HDR. To facilitate wide spread of HDR usage, the backward compatibility of HDR technology with commonly used legacy image storage, rendering, and compression is necessary. Although many tone-mapping algorithms were developed for generating viewable LDR images from HDR content, there is no consensus on which algorithm to use and under which conditions. This paper, via a series of subjective evaluations, demonstrates the dependency of perceived quality of the tonemapped LDR images on environmental parameters and image content. Based on the results of subjective tests, it proposes to extend JPEG file format, as the most popular image format, in a backward compatible manner to also deal with HDR pictures. To this end, the paper provides an architecture to achieve such backward compatibility with JPEG and demonstrates efficiency of a simple implementation of this framework when compared to the state of the art HDR image compression.
Implicit Feedback for Recommender Systems

Can implicit feedback substitute for expli cit ratings in recommender systems? If so, we could avoid the diff iculties associated with gathering explicit ratings from users. How, then, can we capture useful information unobtrusively, and how might we use that information to make recommendations? In this paper we identify three types of impli cit feedback and suggest two strategies for using implicit feedback to make recommendations.
Intramuscular and nerve root stimulation vs lidocaine injection to trigger points in myofascial pain syndrome.

OBJECTIVES
To compare the efficacies of an intramuscular stimulation technique and 0.5% lidocaine injection to trigger points in myofascial pain syndrome.


PARTICIPANTS
Forty-three people with myofascial pain syndrome of the upper trapezius muscle.


INTERVENTIONS
Twenty-two subjects were treated with intramuscular stimulation and another 21 with 0.5% lidocaine injection at all the trigger points on days 0, 7 and 14.


RESULTS
Intramuscular stimulation resulted in a significant reduction in Wong-Baker FACES pain scale scores at all visits and was more effective than trigger point injection. Intramuscular stimulation also resulted in significant improvement on the Geriatric Depression Scale - Short Form. Local twitch responses occurred in 97.7% (42/43) of patients. All the passive cervical ranges of motion were significantly increased. Post-treatment soreness was noted in 54.6% of patients in the intramuscular stimulation group and 38.1% in the trigger point injection group, respectively, and gross subcutaneous haemorrhage (> 4 cm2) was seen in only one patient in the trigger point injection group.


CONCLUSION
In managing myofascial pain syndrome, after one month intramuscular stimulation resulted in more significant improvements in pain intensity, cervical range of motion and depression scales than did 0.5% lidocaine injection of trigger points. Intramuscular stimulation is therefore recommended for myofascial pain syndrome.
Convolutional Neural Networks for Breast Cancer Screening: Transfer Learning with Exponential Decay

In this paper, we propose a Computer Assisted Diagnosis (CAD) system based on a deep Convolutional Neural Network (CNN) model, to build an end-to-end learning process that classifies breast mass lesions. We investigate the impact that has transfer learning when large data is scarce, and explore the proper way to fine-tune the layers to learn features that are more specific to the new data. The proposed approach showed better performance compared to other proposals that classified the same dataset. 1 Background and objectives Breast cancer is the most common invasive disease among women [Siegel et al., 2014] Optimistically, an early diagnosis of the disease increases the chances of recovery dramatically and as such, makes the early detection crucial. Mammography is the recommended screening technique, but it is not enough, we also need the radiologist expertise to check the mammograms for lesions and give a diagnosis, which can be a very challenging task[Kerlikowske et al., 2000]. Radiologists often resort to biopsies and this ends up adding exorbitant expenses to an already burdened patient and health care system [Sickles, 1991]. We propose a Computer Assisted Diagnosis (CAD) system, based on a deep Convolutional Neural Network (CNN) model, designed to be used as a “second-opinion” to help the radiologist give more accurate diagnoses. Deep Learning requires large datasets to train networks of a certain depth from scratch, which are lacking in the medical domain especially for breast cancer. Transfer learning proved to be efficient to deal with little data, even if the knowledge transfer is between two very different domains [Shin et al., 2016]. But still using the technique can be tricky, especially with medical datasets that tend to be unbalanced and limited. And when using the state-of-the art CNNs which are very deep, the models are highly inclined to suffer from overfitting even with the use of many tricks like data augmentation, regularization and dropout. The number of layers to fine-tune and the optimization strategy play a substantial role on the overall performance [Yosinski et al., 2014]. This raises few questions: • Is Transfer Learning really beneficial for this application? • How can we avoid overfitting with our small dataset ? • How much fine-tuning do we need? and what is the proper way to do it? 31st Conference on Neural Information Processing Systems (NIPS 2017), Long Beach, CA, USA. ar X iv :1 71 1. 10 75 2v 1 [ cs .C V ] 2 9 N ov 2 01 7 We investigate the proper way to perform transfer learning and fine-tuning, which will allow us to take advantage of the pre-trained weights and adapt them to our task of interest. We empirically analyze the impact of the fine-tuned fraction on the final results, and we propose to use an exponentially decaying learning rate to customize all the pre-trained weights from ImageNet[Deng et al., 2009] and make them more suited to our type of data. The best model can be used as a baseline to predict if a new “never-seen” breast mass lesion is benign or malignant.
Student Reading Practices in Print and Electronic Media

This paper reports a diary-based qualitative study on college students' reading habits with regard to print and electronic media. Students used a form to record information about their reading practices for twelve days, including length of reading event, location, format used and the purpose of reading. Students tended to use print for academic and long-form reading and to engage with it more deeply. Although electronic resources were sometimes used for academic purposes, students often used them for shorter and non-academic reading. Students found electronic media convenient, but most of them did not wish to switch to electronic media for their academic reading.
Inductive matrix completion for predicting gene–disease associations

MOTIVATION
Most existing methods for predicting causal disease genes rely on specific type of evidence, and are therefore limited in terms of applicability. More often than not, the type of evidence available for diseases varies-for example, we may know linked genes, keywords associated with the disease obtained by mining text, or co-occurrence of disease symptoms in patients. Similarly, the type of evidence available for genes varies-for example, specific microarray probes convey information only for certain sets of genes. In this article, we apply a novel matrix-completion method called Inductive Matrix Completion to the problem of predicting gene-disease associations; it combines multiple types of evidence (features) for diseases and genes to learn latent factors that explain the observed gene-disease associations. We construct features from different biological sources such as microarray expression data and disease-related textual data. A crucial advantage of the method is that it is inductive; it can be applied to diseases not seen at training time, unlike traditional matrix-completion approaches and network-based inference methods that are transductive.


RESULTS
Comparison with state-of-the-art methods on diseases from the Online Mendelian Inheritance in Man (OMIM) database shows that the proposed approach is substantially better-it has close to one-in-four chance of recovering a true association in the top 100 predictions, compared to the recently proposed Catapult method (second best) that has <15% chance. We demonstrate that the inductive method is particularly effective for a query disease with no previously known gene associations, and for predicting novel genes, i.e. genes that are previously not linked to diseases. Thus the method is capable of predicting novel genes even for well-characterized diseases. We also validate the novelty of predictions by evaluating the method on recently reported OMIM associations and on associations recently reported in the literature.


AVAILABILITY
Source code and datasets can be downloaded from http://bigdata.ices.utexas.edu/project/gene-disease.
Global optimization and simulated annealing

In this paper we are concerned with global optimization, which can be defined as the problem of finding points on a bounded subset of IRn in which some real valued functionf assumes its optimal (i.e. maximal or minimal) value. We present a stochastic approach which is based on the simulated annealing algorithm. The approach closely follows the formulation of the simulated annealing algorithm as originally given for discrete optimization problems. The mathematic formulation is extended to continuous optimization problems and we prove asymptotic convergence to the set of global optima. Furthermore, we discuss an implementation of the algorithm and compare its performance with other well known algorithms. The performance evaluation is carried out for a standard set of test functions from the literature. keywords: global optimization, continuous variables, simulated annealing.
LibGuides: 7HASS - Ancient Rome: Key Groups

Learn all about the political, economic and social systems of Ancient Rome and how they have influenced our world today.
Serum uric acid independently predicts cardiovascular events in advanced nephropathy.

BACKGROUND
Chronic kidney disease (CKD) is associated with increased risk for cardiovascular (CV) disease and is also associated with elevated uric acid, which is emerging as a nontraditional CV risk factor. We therefore evaluated uric acid as a risk factor for CV disease in subjects presenting to nephrologists with CKD who were not on medications known to alter endothelial function.


METHODS
303 subjects with stage 3-5 CKD were followed for a mean of 39 months (range 6-46) and assessed for fatal and nonfatal CV events. Hyperuricemia was defined as uric acid >6.0 mg/dl for women and >7.0 mg/dl for men. In addition to other CV risk factors, endothelial function (flow-mediated dilatation), inflammatory markers (hsCRP), and insulin resistance (HOMA index and fasting insulin levels) were included in the analysis. We evaluated the association between uric acid and flow-mediated dilatation with linear regression. The impact of uric acid on composite CV events was assessed with Cox regression analysis.


RESULTS
Of a total of 303 patients, 89 had normouricemia and 214 had hyperuricemia. Both fatal (32 of 214 vs. 1 of 89 subjects) and combined fatal and nonfatal (100 of 214 vs. 13 of 89 subjects) CV events were more common in subjects with hyperuricemia compared with normal uric acid levels, and this was independent of estimated glomerular filtration rate, traditional CV risk factors including diabetes, hypertension and BMI, and nontraditional risk factors (hsCRP and endothelial function). The 46-month survival rate was 98.7% in the group with low uric acid compared to 85.8% in patients with high uric acid (p = 0.002).


CONCLUSIONS
Hyperuricemia is an independent risk factor for CV events in subjects presenting with CKD who are not on medications known to alter endothelial function.
A seismic study of deep structure in South Wales using quarry blasts

Summary. Results are presented from five long seismic profiles in South Wales based on recordings of quarry blasts. Interpretation by means of planar layer modelling, time term analysis and ray tracing provides information on depths to an assumed Precambrian igneous/metamorphic basement and on the thickness of overlying concealed Lower Palaeozoic (? and Upper Proterozoic) sequences. Basement culminations are identified under the western part of the South Wales coalfield and in the Carmarthen Bay area; under parts of the coalfield the Lower Palaeozoic must be thin or absent. The basement is at a depth of 5 km or more under Cower and the Vale of Glamorgan and in adjacent parts of the Bristol Channel, and thick Lower Palaeozoic sequences must be present in these areas. The basement velocity of 6.0–6.3 km s−1 compares well with the low upper crustal velocities encountered along adjacent parts of the lithospheric seismic profile across Britain (LISPB 1974).
Security and privacy for augmented reality systems

AR systems pose potential security concerns that should be addressed before the systems become widespread.