LLukas22/scidocs huggingface dataset:
Idiopathic intracranial hypertension in men.

OBJECTIVE
To compare the characteristics of idiopathic intracranial hypertension (IIH) in men vs women in a multicenter study.


METHODS
Medical records of all consecutive patients with definite IIH seen at three university hospitals were reviewed. Demographics, associated factors, and visual function at presentation and follow-up were collected. Patients were divided into two groups based on sex for statistical comparisons.


RESULTS
We included 721 consecutive patients, including 66 men (9%) and 655 women (91%). Men were more likely to have sleep apnea (24% vs 4%, p < 0.001) and were older (37 vs 28 years, p = 0.02). As their first symptom of IIH, men were less likely to report headache (55% vs 75%, p < 0.001) but more likely to report visual disturbances (35% vs 20%, p = 0.005). Men continued to have less headache (79% vs 89%, p = 0.01) at initial neuro-ophthalmologic assessment. Visual acuity and visual fields at presentation and last follow-up were significantly worse among men. The relative risk of severe visual loss for men compared with women was 2.1 (95% CI 1.4-3.3, p = 0.002) for at least one eye and 2.1 (95% CI 1.1-3.7, p = 0.03) for both eyes. Logistic regression supported sex as an independent risk factor for severe visual loss.


CONCLUSION
Men with idiopathic intracranial hypertension (IIH) are twice as likely as women to develop severe visual loss. Men and women have different symptom profiles, which could represent differences in symptom expression or symptom thresholds between the sexes. Men with IIH likely need to be followed more closely regarding visual function because they may not reliably experience or report other symptoms of increased intracranial pressure.
Music Transcription Using Deep Learning

Music transcription, as an essential component in music signal processing, contributes to wide applications in musicology, accelerates the development of commercial music industry, facilitates the music education as well as benefits extensive music lovers. However, the work relies on a lot of manual work due to heavy requirements on knowledge and experience. This project mainly examines two deep learning methods, DNN and LSTM, to automatize music transcription. We transform the audio files into spectrograms using constant Q transform and extract features from the spectrograms. Deep learning methods have the advantage of learning complex features in music transcription. The promising results verify that deep learning methods are capable of learning specific musical properties, including notes and rhythms. Keywords—automatic music transcription; deep learning; deep neural network (DNN); long shortterm memory networks (LSTM)
A prospective, randomized, comparative trial evaluating respiratory depression during patient-controlled versus anesthesiologist-administered propofol-remifentanil sedation for elective colonoscopy.

BACKGROUND
Patient-controlled sedation (PCS) with propofol-remifentanil (PR) is associated with rapid sedation and recovery, but it is associated with a greater requirement for airway rescue than PCS with midazolam-fentanyl.


OBJECTIVE
To demonstrate that respiratory depression associated with PR is more frequent during anesthesiologist-administered sedation (AAS) than during PCS.


DESIGN
Prospective, randomized, open-label study.


SETTING
Academic medical center.


PATIENTS
Fifty patients undergoing elective colonoscopy.


INTERVENTION
PCS or AAS using PR. All patients breathed 100% oxygen via an anesthesia mask with continuous spirometry and bispectral index (BIS).


MAIN OUTCOME MEASUREMENTS
Respiratory rate and BIS.


RESULTS
Colonoscopy was completed in all patients. No patient under PCS required airway rescue. Five patients under AAS required bag-mask ventilation to resolve Sao(2) (arterial oxygen saturation) less than 90% lasting longer than 30 seconds. The median BIS for the AAS group was 71.7 (range 61.06-82.34) and 88.1 (range 83.15-93.05) for the PCS group. Median respiratory rates were 5.97 (range 1.21-10.73) breaths per minute for AAS and 13.19 (range 9.54-16.84) for PCS. Respiratory rates less than 2 breaths per minute composed 28% of the procedure time for AAS, but only 5% for PCS. Patients under PCS had lower median predicted effect site concentrations for PR, but were able to achieve brief peak levels exceeding those with AAS. These differences were significant (P < .001).


LIMITATIONS
Potential for bias with AAS.


CONCLUSIONS
Patients undergoing colonoscopy with PR are significantly more likely to require intervention for hypoventilation compared with PCS. (


CLINICAL TRIAL REGISTRATION NUMBER
NCT00868920.).
Smoking in eating disorders.

OBJECTIVE
Smoking has been reported as an appetite and weight control method in eating disorders; however, few studies have explored patterns of smoking across subtypes of eating disorders. The aim of this paper was to explore the patterns and prevalence of smoking behavior in 1,524 women from two of the multisite Price Foundation Genetic studies.


METHOD
Smoking behavior was assessed in 306 individuals with anorexia nervosa-restricting type (RAN), 186 with anorexia nervosa-purging type (PAN), 180 with anorexia nervosa and bulimia nervosa (ANBN), 107 with anorexia nervosa-binging type (BAN), 71 individuals with purging type-bulimia nervosa (PBN), and 674 female community controls. We compared smoking prevalence and smoking behaviors across eating disorder (ED) subtypes and in comparison to controls using the Fagerstrom Test of Nicotine Dependence (FTND).


RESULTS
Overall, women with eating disorders reported higher rates of smoking and greater nicotine dependence than controls. Women with binge/purge subtypes of eating disorders reported the highest rates of smoking of all of the subtypes. Smoking in eating disorders was related to impulsive personality traits.


CONCLUSIONS
Women with eating disorders appear to be at increased risk for smoking, particularly those who binge eat and/or purge and display impulsive personality characteristics. Given the high prevalence, the impact of ongoing smoking on maintenance of eating disorders symptoms is worthy of both clinical and research attention.
The influence of a technology-rich classroom environment on elementary teachers' pedagogy and children's learning

Our goal is to investigate the role of ICT within the complex inter-relationships amongst aspects of the classroom setting which contribute to young children’s activity and learning. This paper focuses on the relationships between the many different features of the classroom which influence learning. These include the teacher’s plans and classroom organisation, the way in which the teacher mediates subject knowledge and ICT use for pupils, the children’s ICT capability, the nature of the tasks set and specific learning materials available, the software applications and digital resources available for both staff and children, and other aspects of the classroom environment. The influence of the technology’s features on teaching approaches and pupil learning was explored through classroom observation of teacher and pupil activity in the ‘core’ subjects English, Mathematics and Science in years 3 and 4 (aged 7-9 years), together with interviews with the class teachers. The data has been analysed using an established model for characterising ICT-based pedagogy based on teacher orchestration of the affordances and constraints of classroom resources. We set out the common features of the relationships found across the different classes, and make comparisons between subjects and classes. We draw conclusions concerning the teachers’ pedagogies together with pupil tasks and classroom organisation strategies which create effective learning environments involving the use of ICT and other resources.
Approximate Inference for Deep Latent Gaussian Mixtures

Deep latent Gaussian models (DLGMs) composed of density and inference networks [14]—the pipeline that defines a Variational Autoencoder [8]—have achieved notable success on tasks ranging from image modeling [3] to semi-supervised classification [6, 11]. However, the approximate posterior in these models is usually chosen to be a factorized Gaussian, thereby imposing strong constraints on the posterior form and its ability to represent the true posterior, which is often multimodal. Recent work has attempted to improve the quality of the posterior approximation by altering the Stochastic Gradient Variational Bayes (SGVB) optimization objective. Burda et al. [2] proposed an importance weighted objective, and Li and Turner [10] then generalized the importance sampling approach to a family of α-divergences. Yet, changing the optimization objective is not the only way to attenuate posterior restrictions. Instead, the posterior form itself can be made richer. For instance, Kingma et al. [7] employ full-covariance Gaussian posteriors, and Nalisnick & Smyth [13] use (truncated) GEM random variables. This paper continues this later line of work by using a Gaussian mixture latent space. We describe learning and inference for not only the traditional mixture model but also Dirichlet Process mixtures [1] (with posterior truncation). Our deep Latent Gaussian mixture model (DLGMM) generalizes previous work such as Factor Mixture Analysis [12] and Deep Gaussian Mixtures [15] to arbitrary differentiable inter-layer transformations.
A decade of reconfigurable computing: a visionary retrospective

The paper surveys a decade of R&D on coarse grain reconfigurable hardware and related CAD, points out why this emerging discipline is heading toward a dichotomy of computing science, and advocates the introduction of a new soft machine paradigm to replace CAD by compilation. 1. Introduction Rapidly increasing number and attendance [1] of conferences on re-configurable computing and the adoption of this topic area by congresses like ASP-DAC, DAC, DATE, ISCAS, SPIE, and others indicate, that reconfigurable platforms are heading from niche to mainstream, bridging the gap between ASICs and microprocessors (fig. 2). It's time to revisit R&D results: the goal of this paper. (On the implementation status of some projects we have only incomplete information.). Using FPGAs as accelerator platforms is not subject of this paper. In contrast to FPGA use (fine grain reconfigurable) the area of Reconfigurable Computing mostly stresses the use of coarse grain reconfigurable arrays (RAs) with pathwidths greater than 1 bit, because fine-grained architectures are much less efficient, due to a huge routing area overhead and poor routability [2] [3]. Since computational datapaths have regular structure potential, full custom designs of reconfigurable datapath units (rDPUs) can be drastically more area-efficient, than by assembling the FPGA way from single-bit CLBs. Coarse-grained architectures provide operator level CFBs, word level datapaths, as well as powerful and very area-efficient datapath routing switches. A major benefit is the massive reduction of configuration memory and configuration time, as well as drastic complexity reduction of the P&R (placement and routing) problem. Several architectures will be briefly outlined (also see figure1). Some of them introduce multi-granular solutions, where more coarse granularity can be achieved by bundling of resources, such as e. g. 4 ALUs of 4 bits each to obtain a 16 bit ALU. Mesh-based architectures arrange their PEs mainly as a rectangular 2-D array with horizontal and vertical connections which supports rich communication resources for efficient parallelism. and encourages nearest neighbour (NN) links between adjacent PEs (NN or 4NN: links to 4 sides {east, west, CHESS array: fig. 5). Typically, longer lines are added with different lengths for connections over distances larger than 1. DP-FPGA (Datapath FPGA) [4] has been introduced to implement regularly structured datapaths. It is a FPGA-like mixed fine and coarse grained architecture with 1 and 4 bit paths. Its fabric includes 3 component types: control logic, the datapath, and memory. The datapath block consists of 4 bit-slices: each …
SCN5A mutations associate with arrhythmic dilated cardiomyopathy and commonly localize to the voltage-sensing mechanism.

OBJECTIVES
The aim of this study was to discern the role of the cardiac voltage-gated sodium ion channel SCN5A in the etiology of dilated cardiomyopathy (DCM).


BACKGROUND
Dilated cardiomyopathy associates with mutations in the SCN5A gene, but the frequency, phenotype, and causative nature of these associations remain the focus of ongoing investigation.


METHODS
Since 1991, DCM probands and family members have been enrolled in the Familial Cardiomyopathy Registry and extensively evaluated by clinical phenotype. Genomic deoxyribonucleic acid samples from 338 individuals among 289 DCM families were obtained and screened for SCN5A mutations by denaturing high-performance liquid chromatography and sequence analysis.


RESULTS
We identified 5 missense SCN5A mutations among our DCM families, including novel mutations E446K, F1520L, and V1279I, as well as previously reported mutations D1275N and R222Q. Of 15 SCN5A mutation carriers in our study, 14 (93%) manifested arrhythmia: supraventricular arrhythmia (13 of 15), including sick sinus syndrome (5 of 15) and atrial fibrillation (9 of 15), ventricular tachycardia (5 of 15), and conduction disease (9 of 15).


CONCLUSIONS
Mutations in SCN5A were detected in 1.7% of DCM families. Two-thirds (6 of 9) of all reported DCM mutations in SCN5A localize to the highly conserved homologous S3 and S4 transmembrane segments, suggesting a shared mechanism of disruption of the voltage-sensing mechanism of this channel leading to DCM. Not surprisingly, SCN5A mutation carriers show a strong arrhythmic pattern that has clinical and diagnostic implications.
Skin detection in color images

In this paper, we develop a skin detection algorithm in color images. The r-g color space is used to extract skin color pixels. This approach is motivated by the simplicity and efficient of Hsu's method, which uses a parametric ellipse in a two-dimensional transformed color space. In order to overcome time consuming, we introduce a technique for skin detection which can be applied in a real time system. In this technique, instead of testing each image pixel to label it as skin or non-skin, we skip a set of pixels. The reason of the skipping process is the high probability that neighbors of the non-skin color pixels are also non-skin pixels. The method can rapidly detect skin and non-skin color pixels. Experimental results demonstrate that the proposed method performs well in real images and images databases.
Threading Machine Generated

Viewing email messages as parts of a sequence or a thread is a convenient way to quickly understand their context. Current threading techniques rely on purely syntactic methods, matching sender information, subject line, and reply/forward prefixes. As such, they are mostly limited to personal conversations. In contrast, machine-generated email, which amount, as per our experiments, to more than 60% of the overall email traffic, requires a different kind of threading that should reflect how a sequence of emails is caused by a few related user actions. For example, purchasing goods from an online store will result in a receipt or a confirmation message, which may be followed, possibly after a few days, by a shipment notification message from an express shipping service. In today’s mail systems, they will not be a part of the same thread, while we believe they should. In this paper, we focus on this type of threading that we coin “causal threading”. We demonstrate that, by analyzing recurring patterns over hundreds of millions of mail users, we can infer a causality relation between these two individual messages. In addition, by observing multiple causal relations over common messages, we can generate “causal threads” over a sequence of messages. The four key stages of our approach consist of: (1) identifying messages that are instances of the same email type or“template” (generated by the same machine process on the sender side) (2) building a causal graph, in which nodes correspond to email templates and edges indicate potential causal relations (3) learning a causal relation prediction function, and (4) automatically “threading” the incoming email stream. We present detailed experimental results obtained by analyzing the inboxes of 12.5 million Yahoo! Mail users, who voluntarily opted-in for such research. Supervised editorial judgments show that we can identify more than 70% (recall rate) of all “causal threads”at a precision level of 90%. In addition, for a search scenario we show that we achieve a precision close to 80% at 90% recall. We believe that supporting causal threads in Permission to make digital or hard copies of all or part of thi s work for personal or classroom use is granted without fee provided th at copies are not made or distributed for profit or commercial advantage an d that copies bear this notice and the full citation on the first page. To cop y therwise, to republish, to post on servers or to redistribute to lists, re quires prior specific permission and/or a fee. Copyright 20XX ACM X-XXXXX-XX-X/XX/XX ...$10.00. email clients opens new grounds for improving both email search and browsing experiences.
Comparison of automatic summarisation methods for clinical free text notes

OBJECTIVE
A major source of information available in electronic health record (EHR) systems are the clinical free text notes documenting patient care. Managing this information is time-consuming for clinicians. Automatic text summarisation could assist clinicians in obtaining an overview of the free text information in ongoing care episodes, as well as in writing final discharge summaries. We present a study of automated text summarisation of clinical notes. It looks to identify which methods are best suited for this task and whether it is possible to automatically evaluate the quality differences of summaries produced by different methods in an efficient and reliable way.


METHODS AND MATERIALS
The study is based on material consisting of 66,884 care episodes from EHRs of heart patients admitted to a university hospital in Finland between 2005 and 2009. We present novel extractive text summarisation methods for summarising the free text content of care episodes. Most of these methods rely on word space models constructed using distributional semantic modelling. The summarisation effectiveness is evaluated using an experimental automatic evaluation approach incorporating well-known ROUGE measures. We also developed a manual evaluation scheme to perform a meta-evaluation on the ROUGE measures to see if they reflect the opinions of health care professionals.


RESULTS
The agreement between the human evaluators is good (ICC=0.74, p<0.001), demonstrating the stability of the proposed manual evaluation method. Furthermore, the correlation between the manual and automated evaluations are high (> 0.90 Spearman's rho). Three of the presented summarisation methods ('Composite', 'Case-Based' and 'Translate') significantly outperform the other methods for all ROUGE measures (p<0.05, Wilcoxon signed-rank test and Bonferroni correction).


CONCLUSION
The results indicate the feasibility of the automated summarisation of care episodes. Moreover, the high correlation between manual and automated evaluations suggests that the less labour-intensive automated evaluations can be used as a proxy for human evaluations when developing summarisation methods. This is of significant practical value for summarisation method development, because manual evaluation cannot be afforded for every variation of the summarisation methods. Instead, one can resort to automatic evaluation during the method development process.
Effect of free plant sterols in low-fat milk on serum lipid profile in hypercholesterolemic subjects

Objective: To determine the effect of nonesterified, nonhydrogenated plant sterols solubilized in a partly vegetable oil-filled low-fat milk on serum low-density lipoprotein cholesterol (LDL) in mildly hypercholesterolemic patients.Design: Double-blind, randomized, placebo-controlled three-arm crossover study.Setting: Outpatient clinical trial.Subjects: A total of 138 patients were screened, providing 81 patients for randomization; 71 patients completed the study.Interventions: The study product was a 500 ml milk blend with or without nonesterified, nonhydrogenated sterols. The daily consumption of sterols in the three groups was 0 g/day, control group (C); 1.2 g/day, (Lo); or 1.6 g/day, (Hi), respectively. The patients were randomly assigned to one of three different treatment sequences. Each intervention period was 4 weeks. The total study duration was 12 weeks.Results: The milk product was well tolerated. The placebo-adjusted mean reduction in LDL was 7.13±12.31 and 9.59±12.44% (mean±s.d.) for Lo and Hi groups, respectively (P<0.0001); there was no statistically significant difference in LDL lowering for the Lo and Hi groups. There were no significant changes in serum vitamin E or carotenoid concentrations after standardization with LDL cholesterol during the study period.Conclusion: The present study shows for the first time a substantial reduction in LDL cholesterol with a new, partly vegetable oil-filled 1.2% low-fat milk product, containing nonesterified plant sterols from soybean oil, in a randomized, placebo-controlled trial. This result encourages further development of novel low-fat dairy products containing free plant sterols for future use in cholesterol-lowering initiatives.Sponsorship: The study was financed by Nestec Ltd, Switzerland.
Varicose vein stripping vs haemodynamic correction (CHIVA): a long term randomised trial.

OBJECTIVES
To compare the long-term results of stripping vs. haemodynamic correction (Ambulatory Conservative Haemodynamic Management of Varicose Veins, CHIVA) in the treatment of superficial venous incompetence resulting in chronic venous disease (CVD).


DESIGN
Randomised comparative trial.


PATIENTS
150 patients affected by CVD, CEAP clinical class 2-6, were randomised to saphenous stripping or to CHIVA.


METHODS
The clinical outcome was assessed by an independent observer who recorded the Hobbs clinical score for treated limbs. A subjective report of the outcome was provided by the patients. Recurrence of varices was assessed by both clinical examination and duplex ultrasonography.


RESULTS
The mean follow-up was 10 years, 26 patients were lost to follow-up. The Hobbs score similar in the stripping and CHIVA groups. However recurrence of varicose veins was significantly higher in the stripping group (CHIVA 18%; stripping 35%, P<0.04 Fisher's exact test), without significant differences in the rate of recurrences from the sapheno-femoral junction. The associated risk of recurrence at ten years was doubled in the stripping group (OR 2.2, 95% CI 1-5, P=0.04).


CONCLUSIONS
Recurrent varices occurred more frequently following saphenous stripping than after CHIVA treatment. The deliberate preservation of the saphenous trunk as a route of venous drainage in the CHIVA group may have been a factor reducing the recurrence rate.