LLukas22/scidocs huggingface dataset:
Evaluation of data completeness in the electronic health record for the purpose of patient recruitment into clinical trials: a retrospective analysis of element presence

BACKGROUND
Computerized clinical trial recruitment support is one promising field for the application of routine care data for clinical research. The primary task here is to compare the eligibility criteria defined in trial protocols with patient data contained in the electronic health record (EHR). To avoid the implementation of different patient definitions in multi-site trials, all participating research sites should use similar patient data from the EHR. Knowledge of the EHR data elements which are commonly available from most EHRs is required to be able to define a common set of criteria. The objective of this research is to determine for five tertiary care providers the extent of available data compared with the eligibility criteria of randomly selected clinical trials.


METHODS
Each participating study site selected three clinical trials at random. All eligibility criteria sentences were broken up into independent patient characteristics, which were then assigned to one of the 27 semantic categories for eligibility criteria developed by Luo et al. We report on the fraction of patient characteristics with corresponding structured data elements in the EHR and on the fraction of patients with available data for these elements. The completeness of EHR data for the purpose of patient recruitment is calculated for each semantic group.


RESULTS
351 eligibility criteria from 15 clinical trials contained 706 patient characteristics. In average, 55% of these characteristics could be documented in the EHR. Clinical data was available for 64% of all patients, if corresponding data elements were available. The total completeness of EHR data for recruitment purposes is 35%. The best performing semantic groups were 'age' (89%), 'gender' (89%), 'addictive behaviour' (74%), 'disease, symptom and sign' (64%) and 'organ or tissue status' (61%). No data was available for 6 semantic groups.


CONCLUSIONS
There exists a significant gap in structure and content between data documented during patient care and data required for patient eligibility assessment. Nevertheless, EHR data on age and gender of the patient, as well as selected information on his disease can be complete enough to allow for an effective support of the manual screening process with an intelligent preselection of patients and patient data.
Obstacle Avoidance of Mobile Robot Based on Behavior Hierarchy by Fuzzy Logic

In this paper, we propose a navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using an ultrasonic sensor. Instead of using "sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data, "command fusion" method is used to govern the robot motions. The navigation strategy is based on the combination of fuzzy rules tuned for both goal-approach and obstacle-avoidance. To identify the environments, a command fusion technique is introduced, where the sensory data of ultrasonic sensors and a vision sensor are fused into the identification process. Keywords-mobile robot, command fusion, obstacle avoidance, fuzzy, cost function.
Pyrocarbon interposition wrist arthroplasty in the treatment of failed wrist procedures.

Treatment of failures after prior wrist surgeries with major articular destruction is challenging. In most cases, total wrist fusion is the only possible salvage procedure. We propose a new interposition arthroplasty with a pyrocarbon implant called Amandys. A total of 16 patients, 14 men and 2 women, with a mean age of 56 years were operated on for a failure of wrist surgery performed previously, with an average time lapse of 12 years. The prior surgeries were partial wrist arthrodesis in seven cases, silicone implant interpositions in five cases, advanced Kienböck disease (Lichtman IV) treatment in two cases, proximal row carpectomy in one case, and an isolated scaphoidectomy in one case. A prospective study with clinical and radiological evaluation was performed with a mean follow-up of 24 months (6 to 41 months). Pain and function showed significant improvement. The mean pain score decreased from 7 of 10 to 4 of 10, postoperatively. The mean grip strength was 19 kg (53% of the contralateral side), and the mean range of motion in flexion extension was 68 degrees. Mean strength and range of motion did not change significantly with the operation. The mean QuickDASH (Disability Arm Shoulder and Hand) score decreased from 59 of 100 to 39 of 100. The mean Patient-Rated Wrist Evaluation decreased from 57 of 100 to 33. Two patients (12.5%) required revision for implant repositioning. No dislocation or subsidence of the implant was noted. Pyrocarbon interposition arthroplasty is a new option for treatment of advanced wrist destruction. Preliminary short-term results suggest that it may be a reliable alternative to total wrist fusion. The level of evidence of this study is IV (therapeutic case series).
Forecasting of Financial Markets via Neural Network

Artificial neural network is one of the intelligent methods in Artificial Intelligence. There are many decisions of different tasks using neural network approach. The forecasting problems are high challenge and researchers use different methods to solve them. The financial tasks related to forecasting, classification and management using artificial neural network are considered. The technology and methods for prediction of financial data as well as the developed system for forecasting of financial markets via neural network are described in the paper. The designed architecture of a neural network using four different technical indicators is presented. The developed neural network is used for forecasting movement of stock prices one day ahead and consists of an input layer, one hidden layer and an output layer. The training method is a training algorithm with back propagation of the error. The main advantage of the developed system is self-determination of the optimal topology of neural network, due to which it becomes flexible and more precise. The proposed system with neural network is universal and can be applied to various financial instruments using only basic technical indicators as input data. Key-Words: neural networks, forecasting, training algorithm, financial indicators, backpropagation
TOWARDS A CLOUD-BASED DESIGN AND MANUFACTURING PARADIGM : LOOKING BACKWARD , LOOKING FORWARD

The rise of cloud computing is radically changing the way enterprises manage their information technology (IT) assets. Considering the benefits of cloud computing to the information technology sector, we present a review of current research initiatives and applications of the cloud computing paradigm related to product design and manufacturing. In particular, we focus on exploring the potential of utilizing cloud computing for selected aspects of collaborative design, distributed manufacturing, collective innovation, data mining, semantic web technology, and virtualization. In addition, we propose to expand the paradigm of cloud computing to the field of computer-aided design and manufacturing and propose a new concept of cloud-based design and manufacturing (CBDM). Specifically, we (1) propose a comprehensive definition of CBDM; (2) discuss its key characteristics; (3) relate current research in design and manufacture to CBDM; and (4) identify key research issues and future trends. 1
Dengue dynamics and vaccine cost-effectiveness in Brazil.

Recent Phase 2b dengue vaccine trials have demonstrated the safety of the vaccine and estimated the vaccine efficacy with further trials underway. In anticipation of vaccine roll-out, cost-effectiveness analysis of potential vaccination policies that quantify the dynamics of disease transmission are fundamental to the optimal allocation of available doses. We developed a dengue transmission and vaccination model and calculated, for a range of vaccination costs and willingness-to-pay thresholds, the level of vaccination coverage necessary to sustain herd-immunity, the price at which vaccination is cost-effective and is cost-saving, and the sensitivity of our results to parameter uncertainty. We compared two vaccine efficacy scenarios, one a more optimistic scenario and another based on the recent lower-than-expected efficacy from the latest clinical trials. We found that herd-immunity may be achieved by vaccinating 82% (95% CI 58-100%) of the population at a vaccine efficacy of 70%. At this efficacy, vaccination may be cost-effective for vaccination costs up to US$ 534 (95% CI $369-1008) per vaccinated individual and cost-saving up to $204 (95% CI $39-678). At the latest clinical trial estimates of an average of 30% vaccine efficacy, vaccination may be cost-effective and cost-saving at costs of up to $237 (95% CI $159-512) and $93 (95% CI $15-368), respectively. Our model provides an assessment of the cost-effectiveness of dengue vaccination in Brazil and incorporates the effect of herd immunity into dengue vaccination cost-effectiveness. Our results demonstrate that at the relatively low vaccine efficacy from the recent Phase 2b dengue vaccine trials, age-targeted vaccination may still be cost-effective provided the total vaccination cost is sufficiently low.
Diabetic neuropathies: diagnosis and management.

INTRODUCTION
Changes in human behaviour and lifestyle over the last century have resulted in a dramatic increase in the incidence of diabetes worldwide. Neuropathy is a common and costly complication of both type 1 and type 2 diabetes. The prevalence of neuropathy is estimated to be about 8% in newly diagnosed patients and greater than 50% in patients with long-standing disease. There are two main types of diabetic neuropathies, named as sensorimotor and autonomic neuropathies. Sensorimotor neuropathy is marked by pain, paraesthesia and sensory loss, and autonomic neuropathy may contribute to myocardial infarction, malignant arrhythmia and sudden death.


METHODS
In this article we reviewed the pathogenesis, clinical manifestations diagnosis and treatment of diabetic neuropathies.


CONCLUSION
Sensorimotor and autonomic neuropathies (cardiovascular, gastrointestinal and genitourinary autonomic neuropathies) are common in diabetic patients. Apart from strict glycaemic control, no further therapeutic approach exists in the prevention of this phenomenon. Intensive diabetes therapy, intensive multifactorial cardiovascular risk reduction and lifestyle intervention are recommended in patients with cardiovascular autonomic neuropathy. Gastroparesis is the most debilitating complication of gastrointestinal autonomic neuropathy and genitourinary autonomic neuropathy can cause sexual dysfunction and neurogenic bladder; these conditions are hard to manage. The symptomatic treatment of sensory symptoms includes tricyclic antidepressants, serotonin and norepinephrine reuptake inhibitors, gabapentin, pregabalin and opioids. Other treatment strategies are not so effective.
Fuzzy relevance vector machine for learning from unbalanced data and noise

Handing unbalanced data and noise are two important issues in the field of machine learning. This paper proposed a complete framework of fuzzy relevance vector machine by weighting the punishment terms of error in Bayesian inference process of relevance vector machine (RVM). Above problems can be learned within this framework with different kinds of fuzzy membership functions. Experiments on both synthetic data and real world data demonstrate that fuzzy relevance vector machine (FRVM) is effective in dealing with unbalanced data and reducing the effects of noises or outliers. 2008 Published by Elsevier B.V.
Improvements in symptoms and quality of life in patients with paroxysmal atrial fibrillation treated with radiofrequency catheter ablation versus antiarrhythmic drugs.

BACKGROUND
In patients with paroxysmal atrial fibrillation (AF), catheter ablation maintains sinus rhythm more effectively than antiarrhythmic drugs (AADs), but its effect on symptoms and quality of life (QOL) has not been fully characterized.


METHODS AND RESULTS
We evaluated symptoms and QOL in a multicenter, randomized trial comparing catheter ablation with AADs as second-line treatment for patients with paroxysmal AF. The Short Form (SF)-36 health survey and the AF Symptom Checklist were administered at baseline and 3, 6, and 9 months after a blanking or dose-titration period. The primary between-group comparisons were conducted at 3 months because of permitted crossover from AAD to ablation beyond this time. Additional analyses based on subsequent follow-up were performed, including the construction of mixed linear regression models to assess the impact of multiple factors on follow-up QOL scores. At baseline in both the ablation (n=103) and the AAD (n=56) groups, 7 of 8 SF-36 scales were well below population norms, as were the physical (PCS) and mental (MCS) summary scores. At 3 months, the same 7 SF-36 scales were significantly (P<0.01) higher in the ablation than in the AAD group, as were the PCS (52.0±7.8 versus 47.1±10.6; P<0.01) and MCS (52.4±8.1 versus 46.6±9.8; P<0.01) scores, whereas symptom frequency (9.3±9.2 versus 19.0±12.6; P<0.001) and symptom severity (7.7±7.2 versus 16.2±10.0; P<0.001) were significantly reduced. In multivariable analysis, ablation and recurrent arrhythmias most strongly correlated with QOL changes over time.


CONCLUSIONS
For second-line therapy of paroxysmal AF, ablation is superior to AAD treatment at improving symptoms and QOL.


CLINICAL TRIAL REGISTRATION
URL: http://www.clinicaltrials.gov. Unique identifier: NCT00116428.
NXgraph: An efficient graph processing system on a single machine

Recent studies show that graph processing systems on a single machine can achieve competitive performance compared with cluster-based graph processing systems. In this paper, we present NXgraph, an efficient graph processing system on a single machine. We propose the Destination-Sorted Sub-Shard (DSSS) structure to store a graph. To ensure graph data access locality and enable fine-grained scheduling, NXgraph divides vertices and edges into intervals and sub-shards. To reduce write conflicts among different threads and achieve a high degree of parallelism, NXgraph sorts edges within each sub-shard according to their destination vertices. Then, three updating strategies, i.e., Single-Phase Update (SPU), Double-Phase Update (DPU), and Mixed-Phase Update (MPU), are proposed in this paper. NXgraph can adaptively choose the fastest strategy for different graph problems according to the graph size and the available memory resources to fully utilize the memory space and reduce the amount of data transfer. All these three strategies exploit streamlined disk access patterns. Extensive experiments on three real-world graphs and five synthetic graphs show that NXgraph outperforms GraphChi, TurboGraph, VENUS, and GridGraph in various situations. Moreover, NXgraph, running on a single commodity PC, can finish an iteration of PageRank on the Twitter [1] graph with 1.5 billion edges in 2.05 seconds; while PowerGraph, a distributed graph processing system, needs 3.6s to finish the same task on a 64-node cluster.
Relative Transfer Function Identification Using Convolutive Transfer Function Approximation

In this paper, we present a relative transfer function (RTF) identification method for speech sources in reverberant environments. The proposed method is based on the convolutive transfer function (CTF) approximation, which enables to represent a linear convolution in the time domain as a linear convolution in the short-time Fourier transform (STFT) domain. Unlike the restrictive and commonly used multiplicative transfer function (MTF) approximation, which becomes more accurate when the length of a time frame increases relative to the length of the impulse response, the CTF approximation enables representation of long impulse responses using short time frames. We develop an unbiased RTF estimator that exploits the nonstationarity and presence probability of the speech signal and derive an analytic expression for the estimator variance. Experimental results show that the proposed method is advantageous compared to common RTF identification methods in various acoustic environments, especially when identifying long RTFs typical to real rooms.
Effect of whole-body vibration on muscle strength and balance in diplegic cerebral palsy: a randomized controlled trial.

OBJECTIVE
The purpose of this study was to investigate the effects of whole-body vibration training on muscle strength and balance in children with diplegic cerebral palsy.


DESIGN
Fifteen children were assigned to the experimental group, which received whole-body vibration training (9 mins per day, 5 days per week). Another 15 were assigned to the control group, which participated in a traditional physical therapy exercise program for 3 successive months. Baseline and posttreatment assessments were performed using the Biodex isokinetic dynamometer to evaluate the knee extensors peak torque at 60 degrees per second and 90 degrees per second and using the Biodex balance system to evaluate stability index.


RESULTS
The children in the experimental group showed a significant improvement when compared with those in the control group (P < 0.001). The peak torque at 60 degrees per second and 90 degrees per second after treatment was 28.8 ± 0.45 and 47.5 ± 0.7 N · m and 30.9 ± 0.68 and 54.2 ± 1.7 N · m for the control and the experimental group, respectively. The overall stability index after treatment was 2.75 and 2.2 for the control group and the experimental group, respectively.


CONCLUSIONS
Whole-body vibration training may be a useful tool for improving muscle strength and balance in children with diplegic cerebral palsy.
TGF-β Concentration in Breast Milk is Associated With the Development of Eczema in Infants

Background: Transforming growth factor (TGF)-β in breast milk is crucial for mucosal immune system in the neonatal period. We hypothesized that the level of exposure to TGF-β from breast milk in the first month of life is related to the development of eczema later in life. Thus, the present study investigated whether changes in TGF-β levels between colostrum and mature milk are associated with such occurrence in a birth cohort study. Methods: Colostrum and 1-month breast milk samples were collected from mothers who participated in our birth cohort study. TGF-β1 and TGF-β2 levels in breast milk were measured using a commercial ELISA kit. The development of eczema in the first 6 months after birth was assessed based on parent's response to a questionnaire. Levels of TGF-β1 and TGF-β2 were compared in breast milk from mothers of infants with and without eczema. Results: In children with eczema, TGF-β1 levels were higher in colostrum, but lower in 1-month milk. A lower TGF-β1 ratio (1-month milk/colostrum) was related to the development of eczema during the first 6 months of life. There was no difference in TGF-β2 ratio (1-month milk/colostrum) between eczema group and control group. Conclusions: Concentration of TGF-β1 but not TGF-β2 in breast milk during the first month after birth may be associated with eczema later in life. Factors that increase TGF-β1 levels in breast milk may play a role in preventing allergic disease.
Pig in the middle : farmers and the delivery of farm animal welfare standards

Purpose This paper examines the attitude of UK pig farmers to the delivery of improved farm animal welfare standards and investigates how they contribute to this objective through their membership of a range of different farm assurance schemes. Design/methodology/approach The analysis focuses on three main groups of pig farmers: (i) farmers engaged in conventional farm assurance schemes; (ii) farmers participating in specific animal welfare schemes and (iii) certified organic farmers. Fifty four farmers were interviewed about their participation in farm assurance schemes and their attitudes to animal welfare and towards the retailers and consumers they supply. Each answer was analysed individually and a list of themes identified for each type of scheme. These were compared and synthesised in an overall analysis. Findings The analysis identified how differently or similarly the different groups of farmers viewed the issues related to animal welfare. The findings revealed that while farmers shared some attitudes regardless of the schemes they participated in, there were differences between schemes in certain key areas such as farmers’ motives for participation. Research limitations/implications Although the sample was limited to England (the main focus of pig production in the UK) and was not random, farmers were selected to reflect the geographical distribution of production and the range of relevant schemes. Originality/value of paper This study adds to this limited literature that focuses on farmers’ views, attitudes and perceptions with regard to animal welfare. The paper is of value to stakeholders involved in the food chain who have an interest in animal welfare such as farmers, retailers, consumers and policy-makers.
Taper structures for coupling into photonic crystal slab waveguides

We present an adiabatic taper design in three dimensions for coupling light into photonic crystal defect waveguides in a square lattice of circular dielectric rods. The taper is a two-stage structure in which the first stage makes the transition from a dielectric waveguide to a coupled-cavity waveguide. The second stage subsequently transforms the waveguide mode from an index-guided mode to a band-gap-guided mode. We discuss differences between the two-dimensional device and its three-dimensional slab version. © 2003 Optical Society of America OCIS codes: 060.1810, 130.3120, 230.7370.
Past, Present, and Future of Emergency Dispatch Research: A Systematic Literature Review

Introduction: Emergency dispatch is a relatively new field, but the growth of dispatching as a profession, along with raised expectations for help before responders arrive, has led to increased production of and interest in emergency dispatch research. As yet, no systematic review of dispatch research has been conducted. Objective: This study reviewed the existing literature and indicated gaps in the research as well as potentially fruitful extensions of current lines of study. Methods: Dispatch-related terms were used to search for papers in research databases (including PubMed, MEDLINE, EMBASE, EMCARE, SciSearch, PsychInfo, and SCOPUS). All research papers with dispatching as the core focus were included. Results: A total 149 papers (114 original research, and 35 seminal concept papers) were identified. A vast majority dealt with medical dispatching (as opposed to police or fire dispatching). Four major issues emerged from the early history of emergency dispatch that continue to dominate dispatch studies: dispatch as first point of care, standardization of the dispatching process, resource allocation, and best practices for dispatching. Conclusion: Substantial peer-reviewed research does exist in dispatch studies. However, a lack of consistent metrics, the near-nonexistence of research in fire and police dispatching, and a relative lack of studies in many areas of interest indicate a need for increased participation in research by communication center administrators and others “on the ground” in emergency dispatch, as well as increased collaboration between research organizations and operations personnel.