varunr14/newsummary huggingface dataset:
This study discussed a computer aided program development that meets the requirements of people with physical disabilities . A number of control modes such as electrode signal recorded on the scalp and blink control were combined with the scanning human machine interface to improve the external input output device . Moreover a novel and precise algorithm which filters noise and reduces misrecognition of the system was proposed . A convenient assistive device can assist people with physical disabilities to meet their requirements for independent living and communication with the outside . The traditional scanning keyboard is changed and only the phonetic notations are typed instead of characters thus the time of tone and function selection could be saved and the typing time could be also reduced . Barrier free computer assistive devices and interface for people with physical disabilities in typing or speech could allow them to use a scanning keyboard to select phonetic symbols instead of Chinese characters to express their thoughts . The human machine interface controls can obtain more reliable results as 99.8 connection success rate and 95 typing success rate . 


Summary: A scanning interface with electrical signal detection of the head is designed. A algorithm filters noise and reduces misrecognition of the system. The traditional scanning keyboard is modified. The typing time could be reduced. It can obtain more reliable results as 95 success rate.
The importance of evaluating complications and toxicity during and following treatment has been stressed in many publications . In most studies these endpoints are presented descriptively and summarized by numbers and percentages but descriptive methods are rarely sufficient to evaluate treatment related complications . Pepe and Lancar developed Prevalence and Weighted Prevalence functions which take into account the duration and the severity of complication unlike conventional methods of survival analysis or competing risks which are limited to the time to first event . The purpose of this paper is to describe features and use of two R functions main.preval.func and main.wpreval.func which were designed for the analysis of survival adjusted for quality of life . These functions compute descriptive statistics survival and competing risks analysis and especially Prevalence and Weighted Prevalence estimations with confidence intervals and associated test statistics . The use of these functions is illustrated by several examples . 


Summary: The importance of evaluating complications has been stressed in many publications. Descriptive analysis may not be sufficient to evaluate long term complications. This paper provides two R functions using Prevalence and Weighted Prevalence. This method considers duration and repetitions unlike conventional methods.
Background Developing countries are confronting a steady growth in the prevalence of the infectious diseases . Mobile technologies are widely available and can play an important role in health care at the regional community and individual levels . Although labs usually able to accomplish the requested blood test and produce the results within two days after receiving the samples but the time for the results to be delivered back to clinics is quite variable depending on how often the motorbike transport makes trips between the clinic and the lab . Objective In this study we seek to assess factors facilitating as well as factors hindering the adoption of mobile devices in the Swazi healthcare through evaluating the end users of the LabPush system . Methods A qualitative study with semi structured and in depth one on one interviews were conducted over two month period July August 2012 . Purposive sampling was used participants were those operating and using the LabPush system at the remote clinics at the national laboratory and the supervisors of users at Swaziland . Interview questions were focused on perceived of ease of use and usefulness of the system . All interviews were recorded and then transcribed . Results This study had aimed its primary focus on reducing TAT prompt patient care reducing bouncing of patients and defaulting of patients which were challenges that the clinicians have always had . Therefore the results revealed several barriers and facilitators to the adoption of mobile device by healthcare providers in the Swaziland . The themes Shortens TAT Technical support Patient centered care Mindset Improved communication Missing Reports Workload Workflow Security of smart phone Human error and Ownership are sorted by facilitators to barriers . Conclusion Thus the end users perspective prompt patient care reduced bouncing of patients technical support better communication willing participant and social influence were facilitators of the adoption m health in the Swazi healthcare . 


Summary: This study seeks to assess factors facilitating as well as factors hindering the adoption of mobile devices in the Swazi healthcare. This study evaluated the end users of the LabPush system in Swaziland. This study provides end users perspective prompt patient care reduced bouncing of patients technical support better communication willing participant and social influence were facilitators of the adoption m health in the Swazi healthcare.
Networks permitting anonymous contributions continue to expand and flourish . In some networks the reliability of a contribution is not of particular importance . In other settings however the development of a network is driven by specific purposes which make the reliability of information exchanged of significant importance . One such situation involves the use of information markets for aggregating individuals preferences on new or emerging technologies . At this point there remains skepticism concerning the reliability of the preference revelations in such markets and thus the resulting preference aggregations and rankings of emerging technologies . In this paper we study the reliability of on line preference revelation using a series of controlled laboratory experiments . Our analysis includes individuals pre and post experiment rankings of technologies individual trading and accumulation activities during an electronics market experiment the final experimental market outcomes and a ranking of the same technologies by a panel of experts from a Fortune 5 company . In addition as a final step we allowed each participant to actually select and keep a unit of one of the technologies at zero price . That is we were able to observe each participant s actual final true preference from the set of technologies . 


Summary: Outcome from information market is much consistent with expert panel. Information market does influence individual preferences. There is considerable inconsistency between survey and individual true preferences.
The aim of this study is to design a robust feature extraction method for the classification of multiclass EEG signals to determine valuable features from original epileptic EEG data and to discover an efficient classifier for the features . An optimum allocation based principal component analysis method named as OA PCA is developed for the feature extraction from epileptic EEG data . As EEG data from different channels are correlated and huge in number the optimum allocation scheme is used to discover the most favorable representatives with minimal variability from a large number of EEG data . The principal component analysis is applied to construct uncorrelated components and also to reduce the dimensionality of the OA samples for an enhanced recognition . In order to choose a suitable classifier for the OA PCA feature set four popular classifiers least square support vector machine naive bayes classifier k nearest neighbor algorithm and linear discriminant analysis are applied and tested . Furthermore our approaches are also compared with some recent research work . The experimental results show that the LS SVM 1v1 approach yields 100 of the overall classification accuracy improving up to 7.10 over the existing algorithms for the epileptic EEG data . The major finding of this research is that the LS SVM with the 1v1 system is the best technique for the OA PCA features in the epileptic EEG signal classification that outperforms all the recent reported existing methods in the literature . 


Summary: Development of a novel feature extraction method denoted as OA PCA. Introducing Optimum allocation approach that in our innovative concept to get most representative data points from a time window. Better performances than some existing methods.
Background The report from the Institute of Medicine To Err Is Human Building a Safer Health System in 1999 drew a special attention towards preventable medical errors and patient safety . The American Reinvestment and Recovery Act of 2009 and federal criteria of Meaningful use stage 1 mandated e prescribing to be used by eligible providers in order to access Medicaid and Medicare incentive payments . Inappropriate prescribing has been identified as a preventable cause of at least 20 of drug related adverse events . A few studies reported system related errors and have offered targeted recommendations on improving and enhancing e prescribing system . Objective This study aims to enhance efficiency of the e prescribing system by shortening the medication list reducing the risk of inappropriate selection of medication as well as in reducing the prescribing time of physicians . Method 103.48 million prescriptions from Taiwan s national health insurance claim data were used to compute Diagnosis Medication association . Furthermore 100 000 prescriptions were randomly selected to develop a smart medication recommendation model by using association rules of data mining . Results and conclusion The important contribution of this model is to introduce a new concept called Mean Prescription Rank of prescriptions and Coverage Rate of prescriptions . A proactive medication list was computed using MPR and CR . With this model the medication drop down menu is significantly shortened thereby reducing medication selection errors and prescription times . The physicians will still select relevant medications even in the case of inappropriate selection . 


Summary: This model is to introduce a new concept called Mean Prescription Rank of prescriptions. The physicians will able to select relevant medications even in the case of inappropriate unintentional selection. To enhance efficiency of the e prescribing system.
At about the same time R. Liu introduced the notion of simplicial depth and R. Randles the notion of interdirections . These completely independent and seemingly unrelated initiatives serving different purposes in nonparametric multivariate analysis have spawned significant activity within their quite different respective domains . A surprising and fruitful connection between the two notions is shown . Exploiting the connection statistical procedures based on interdirections can be modified to use simplicial depth instead at considerable reduction of computational burden in the case of dimensions 2 3 and 4 . Implications regarding multivariate sign test statistics are discussed in detail and several other potential applications are noted . 


Summary: An important connection between Liu s simplicial depth and Randles interdirections. Computational advantage of simplicial depth over interdirections. Basis for profitably modifying statistical procedures based on interdirections. New perspectives on multivariate sign tests.
In this paper we propose a new method for skin detection in color images which consists in spatial analysis using the introduced texture based discriminative skin presence features . Color based skin detection has been widely explored and many skin color modeling techniques were developed so far . However efficacy of the pixel wise classification is limited due to an overlap between the skin and non skin pixels reported in many color spaces . To increase the discriminating power of the skin classification schemes textural and spatial features are often exploited for skin modeling . Our contribution lies in using the proposed discriminative feature space as a domain for spatial analysis of skin pixels . Contrary to existing approaches we extract the textural features from the skin probability maps rather than from the luminance channel . Presented experimental study confirms that the proposed method outperforms alternative skin detection techniques which also involve analysis of textural and spatial features . 


Summary: The skin probability maps are refined using discriminative features DSPFs . Spatial analysis of skin pixels is more successful when performed in DSPF skin maps. The textural features are extracted from skin maps rather than from the grayscale.
Automated fracture detection is an essential part of a computer aided tele medicine system . In this paper we have proposed a unified technique for the detection and evaluation of orthopaedic fractures in long bone digital X ray image . We have also developed a software tool that can be conveniently used by paramedics or specialist doctors . The proposed tool first segments the bone region of an input digital X ray image from its surrounding flesh region and then generates the bone contour using an adaptive thresholding approach . Next it performs unsupervised correction of bone contour discontinuities that might have been generated because of segmentation errors and finally detects the presence of fracture in the bone . Moreover the method can also localize the line of break for easy visualization of the fracture identify its orientation and assess the extent of damage in the bone . Several concepts from digital geometry such as relaxed straightness and concavity index are utilized to correct contour imperfections and to detect fracture locations and type . Experiments on a database of several long bone digital X ray images show satisfactory results . 


Summary: Input Bone X ray image. Output Segmentation of bone contour from the surrounding region. Correct false discontinuities in the bone contour based on digital geometry. Generate an isothetic outer cover of the bone contour. Identify fracture points and the line of fracture.
Background and objective Cardiac arrhythmias are disorders in terms of speed or rhythm in the heart s electrical system . Atrial fibrillation is the most common sustained arrhythmia that affects a large number of persons . Electrophysiologic study procedures are used to study fibrillation in patients they consist of inducing a controlled fibrillation in surgical room to analyze electrical heart reactions or to decide for implanting medical devices . Nevertheless the spontaneous induction may generate an undesired AFib which may induce risk for patient and thus a critical issue for physicians . We study the unexpected AFib onset aiming to identify signal patterns occurring in time interval preceding an event of spontaneous fibrillation . Profiling such signal patterns allowed to design and implement an AFib prediction algorithm able to early identify a spontaneous fibrillation . The objective is to increase the reliability of EPS procedures . Methods We gathered data signals collected by a General Electric Healthcare s CardioLab electrophysiology recording system . We extracted superficial and intracavitary cardiac signals regarding 50 different patients studied at the University Magna Graecia Cardiology Department . By studying waveform of intracavitary signals before the onset of the arrhythmia we were able to define patterns related to AFib onsets that are side effects of an inducted fibrillation . Results A framework for atrial fibrillation prediction during electrophysiological studies has been developed . It includes a prediction algorithm to alert an upcoming AFib onset . Tests have been performed on an intracavitary cardiac signals data set related to patients studied in electrophysiological room . Also results have been validated by the clinicians proving that the framework can be useful in case of integration with the polygraph helping physicians in managing and controlling of patient status during EPS . 


Summary: HRV analysis designed to work with R wave also works on A waves. pre AFib signal portions are predictive of spontaneous AFib onset. An automatic device to alert the physician about an incoming AFib onset can be built.
Interpenetrated polymer networks composed by two independent polymeric networks that spatially interpenetrate are considered as valuable systems to control permeability and mechanical properties of hydrogels for biomedical applications . Specifically poly poly IPNs have been explored as good hydrogels for mimicking articular cartilage . These lattices are proposed as matrix implants in cartilage damaged areas to avoid the discontinuity in flow uptake preventing its deterioration . The permeability of these implants is a key parameter that influences their success by affecting oxygen and nutrient transport and removing cellular waste products to healthy cartilage . Experimental try and error approaches are mostly used to optimize the composition of such structures . However computational simulation may offer a more exhaustive tool to test and screen out biomaterials mimicking cartilage avoiding expensive and time consuming experimental tests . An accurate and efficient prediction of material s permeability and internal directionality and magnitude of the fluid flow could be highly useful when optimizing biomaterials design processes . Here we present a 3D computational model based on Sussman Bathe hyperelastic material behaviour . A fluid structure analysis is performed with ADINA software considering these materials as two phases composites where the solid part is saturated by the fluid . The model is able to simulate the behaviour of three non biodegradable hydrogel compositions where percentages of PEA and PHEA are varied . Specifically the aim of this study is to verify the validity of the Sussman Bathe material model to simulate the response of the PEA PHEA biomaterials to predict the fluid flux and the permeability of the proposed IPN hydrogels and to study the material domains where the passage of nutrients and cellular waste products is reduced leading to an inadequate flux distribution in healthy cartilage tissue . The obtained results show how the model predicts the permeability of the PEA PHEA hydrogels and simulates the internal behaviour of the samples and shows the distribution and quantification of fluid flux . 


Summary: A 3D computational model to study the behaviour of interpenetrated polymer networks IPNs for cartilage repairing is proposed. The model can predict the permeability of the poly ethyl acrylate PEA poly 2 hydroxyethyl acrylate PHEA IPNs. The model is able to simulate the internal distribution and quantification of fluid flux of the two phases composite. The model enables us to study the nutrient supply within the different biomaterial regions.
Background and objective The accurate identification of fat droplets is a prerequisite for the automatic quantification of steatosis in histological images . A major challenge in this regard is the distinction between clustered fat droplets and vessels or tissue cracks . Methods We present a new method for the identification of fat droplets that utilizes adjacency statistics as shape features . Adjacency statistics are simple statistics on neighbor pixels . Results The method accurately identified fat droplets with sensitivity and specificity values above 90 . Compared with commonly used shape features adjacency statistics greatly improved the sensitivity toward clustered fat droplets by 29 and the specificity by 17 . On a standard personal computer megapixel images were processed in less than 0.05s . Conclusions The presented method is simple to implement and can provide the basis for the fast and accurate quantification of steatosis . 


Summary: A new method for identifying fat droplets in histological images is presented. Adjacency statistics are utilized as shape features. Fat droplets are identified with high sensitivity and specificity. Adjacency statistics greatly improve the identification of clustered fat droplets. The method can be quickly executed on standard computers.
The increasing complexity of VLSI digital systems has dramatically supported system level representations in modeling and design activities . This evolution makes often necessary a compliant rearrangement of the modalities followed in validation and analysis tasks as in the case of power performances estimation . Nowadays transaction level paradigms are having a wider and wider consideration in the research on electronic system level design techniques . With regard to the available modeling resources the most relevant framework is probably the transaction level extension of the SystemC language which therefore represents the best platform for defining transaction level design techniques . In this paper we present a macro modeling power estimation methodology valid for SystemC TLM prototypes and of general applicability . The present discussion illustrates the implementation modalities of the proposed approach verifying its effectiveness through a comparison with RTL estimation techniques . 


Summary: The paper deals with power analysis on transaction level models of complex digital systems. We propose an estimation methodology strictly based on the modeling constructs of SystemC TLM and of general applicability. We consider the comparison with RTL power estimation techniques on several design aspects estimation accuracy simulation time and modeling effort The experimental results show the design advantages of the proposed methodology with respect to RTL estimation techniques.
The visualization of multiple 3D objects has been increasingly required for recent applications in medical fields . Due to the heterogeneity in data representation or data configuration it is difficult to efficiently render multiple medical objects in high quality . In this paper we present a novel intermixing scheme for fusion rendering of multiple medical objects while preserving the real time performance . First we present an in slab visibility interpolation method for the representation of subdivided slabs . Second we introduce virtual zSlab which extends an infinitely thin boundary into a slab with a finite thickness . Finally based on virtual zSlab and in slab visibility interpolation we propose a slab based visibility intermixing method with the newly proposed rendering pipeline . Experimental results demonstrate that the proposed method delivers more effective multiple object renderings in terms of rendering quality compared to conventional approaches . And proposed intermixing scheme provides high quality intermixing results for the visualization of intersecting and overlapping surfaces by resolving aliasing and z fighting problems . Moreover two case studies are presented that apply the proposed method to the real clinical applications . These case studies manifest that the proposed method has the outstanding advantages of the rendering independency and reusability . 


Summary: A novel intermixing scheme is proposed for fusion rendering of multiple medical objects. High quality intermixing results are acquired for intersecting and overlapping surfaces. Our method resolved aliasing and z fighting problems.