varunr14/newsummary huggingface dataset:
Cardiopulmonary resuscitation is a first aid key survival technique used to stimulate breathing and keep blood flowing to the heart . Its effective administration can significantly increase the chances of survival for victims of cardiac arrest . LISSA is a serious game designed to complement CPR teaching and also to refresh CPR skills in an enjoyable way . The game presents an emergency situation in a 3D virtual environment and the player has to save the victim applying the CPR actions . In this paper we describe LISSA and its evaluation in a population composed of 109 nursing undergraduate students enrolled in the Nursing degree of our university . To evaluate LISSA we performed a randomized controlled trial that compares the classical teaching methodology composed of self directed learning for theory plus laboratory sessions with a mannequin for practice with the one that uses LISSA after self directed learning for theory and before laboratory sessions with a mannequin . From our evaluation we observed that students using LISSA gave significantly better learning acquisition scores than those following traditional classes . To evaluate the differences between students of these groups we performed a paired samples t test between Group 1 and 2 and between students of Group 1 and 3 . From these tests we observed that there are significant differences in both cases . We also evaluated student performance of main steps of CPR protocol . Students that use LISSA performed better than the ones that did not use it . 


Summary: LISSA is a serious game designed to complement CPR teaching in an enjoyable way. LISSA has been evaluated in a population 109 nursing undergraduate students. Students using LISSA gave significantly better learning acquisition scores than those following traditional classes. Students that use LISSA performed the CPR protocol better than the ones that did not use it.
Glaucoma is an optic neuropathy which is one of the main causes of permanent blindness worldwide . This paper presents an automatic image processing based method for detection of glaucoma from the digital fundus images . In this proposed work the discriminatory parameters of glaucoma infection such as cup to disc ratio neuro retinal rim area and blood vessels in different regions of the optic disc has been used as features and fed as inputs to learning algorithms for glaucoma diagnosis . These features which have discriminatory changes with the occurrence of glaucoma are strategically used for training the classifiers to improve the accuracy of identification . The segmentation of optic disc and cup based on adaptive threshold of the pixel intensities lying in the optic nerve head region . Unlike existing methods the proposed algorithm is based on an adaptive threshold that uses local features from the fundus image for segmentation of optic cup and optic disc making it invariant to the quality of the image and noise content which may find wider acceptability . The experimental results indicate that such features are more significant in comparison to the statistical or textural features as considered in existing works . The proposed work achieves an accuracy of 94.11 with a sensitivity of 100 . A comparison of the proposed work with the existing methods indicates that the proposed approach has improved accuracy of classification glaucoma from a digital fundus which may be considered clinically significant . 


Summary: The optic nerve head region is analyzed for glaucoma diagnosis. Adaptive threshold based segmentation of optic disc and cup is implemented. CDR NRR and blood vessel area as per ISNT rule are selected as features. An accuracy of 94.11 with sensitivity of 100 is achieved using SVM classifier.
Extended Chebyshev spaces that also comprise the constants represent large families of functions that can be used in real life modeling or engineering applications that also involve important integral or rational curves and surfaces . Concerning CAGD the unique normalized B bases of such vector spaces ensure optimal shape preserving properties important evaluation or subdivision algorithms and useful shape parameters . Therefore we propose global explicit formulas for the entries of those transformation matrices that map these normalized B bases to the traditional bases of the underlying vector spaces . Then we also describe general and ready to use control point configurations for the exact representation of those traditional integral parametric curves and surfaces that are specified by coordinate functions given as linear combinations of ordinary basis functions . The obtained results are also extended to the control point and weight based exact description of the rational counterpart of these integral parametric curves and surfaces . The universal applicability of our methods is presented through polynomial trigonometric hyperbolic or mixed extended Chebyshev vector spaces . 


Summary: We consider extended Chebyshev spaces that also comprise the constant functions. We transform the unique normalized B bases of these spaces to their ordinary ones. The proposed general basis transformation is based only on endpoint derivatives. Ordinary curves surfaces can be described by explicit control point based formulas. Our formulas can be more efficient than other numerical methods up to dimension 16.
It is desirable to reduce the excessive radiation exposure to patients in repeated medical CT applications . One of the most effective ways is to reduce the X ray tube current or tube voltage . However it is difficult to achieve accurate reconstruction from the noisy measurements . Compared with the conventional filtered back projection algorithm leading to the excessive noise in the reconstructed images the approaches using statistical iterative reconstruction with low mAs show greater image quality . To eliminate the undesired artifacts and improve reconstruction quality we proposed in this work an improved SIR algorithm for low dose CT reconstruction constrained by a modified Markov random field regularization . Specifically the edge preserving total generalized variation which is a generalization of total variation and can measure image characteristics up to a certain degree of differentiation was introduced to modify the MRF regularization . In addition a modified alternating iterative algorithm was utilized to optimize the cost function . Experimental results demonstrated that images reconstructed by the proposed method could not only generate high accuracy and resolution properties but also ensure a higher peak signal to noise ratio in comparison with those using existing methods . 


Summary: Proposed a novel regularization scheme MMRF for CT reconstruction. Present a new objective function and deduce its iterative equation. Optimize the objective function by a modified alternative iterative algorithm. Design experiments on different phantoms to validate the validity of the approach. Analyze the results by visual evaluation and quantitative evaluation.
We propose the signal processing technique of calculating a cross correlation function and an average deviation between the continuous blood glucose and the interpolation of limited blood glucose samples to evaluate blood glucose monitoring frequency in a self aware patient software agent model . The diabetic patient software agent model is a 24 h circadian self aware stochastic model of a diabetic patient s blood glucose levels in a software agent environment . The purpose of this work is to apply a signal processing technique to assist patients and physicians in understanding the extent of a patient s illness using a limited number of blood glucose samples . A second purpose of this work is to determine an appropriate blood glucose monitoring frequency in order to have a minimum number of samples taken that still provide a good understanding of the patient s blood glucose levels . For society in general the monitoring cost of diabetes is an extremely important issue and these costs can vary tremendously depending on monitoring approaches and monitoring frequencies . Due to the cost and discomfort associated with blood glucose monitoring today patients expect monitoring frequencies specific to their health profile . The proposed method quantitatively assesses various monitoring protocols in nine predefined categories of patient agents in terms of risk factors of health status and age . Simulation results show that sampling 6 times per day is excessive and not necessary for understanding the dynamics of the continuous signal in the experiments . In addition patient agents in certain conditions only need to sample their blood glucose 1 time per week to have a good understanding of the characteristics of their blood glucose . Finally an evaluation scenario is developed to visualize this concept in which appropriate monitoring frequencies are shown based on the particular conditions of patient agents . This base line can assist people in determining an appropriate monitoring frequency based on their personal health profile . 


Summary: A cross correlation function and an average deviation between the continuous blood glucose and the interpolation of limited blood glucose samples are calculated. This model evaluates blood glucose monitoring frequency in a self aware patient software agent model. This model provides diabetes patients and physicians a good understanding of the illness from limited blood glucose samples. We propose a new way to determine an appropriate blood glucose monitoring frequency to reduce the cost and discomfort associated with blood glucose monitoring. We propose a base line to assist people to determine an individual appropriate monitoring frequency based on their situations.
The intraclass correlation coefficient in a two way analysis of variance is a ratio involving three variance components . Two recently developed methods for constructing confidence intervals for the ICC are the Generalized Confidence Interval and Modified Large Sample methods . The resulting intervals have been shown to maintain nominal coverage . But methods for determining sample size for GCI and MLS intervals are lacking . Sample size methods that guarantee control of the mean width for GCI and MLS intervals are developed . In the process two variance reduction methods are employed called dependent conditioning and inverse Rao Blackwellization . Asymptotic results provide lower bounds for mean CI widths and show that MLS and GCI widths are asymptotically equivalent . Simulation studies are used to investigate the new methods . A real data example is used and application issues discussed . The new methods are shown to result in adequate sample size estimates the asymptotic estimates are accurate and the variance reduction techniques are effective . A sample size program is developed . R program can be downloaded at http dobbinuga.com . Future extensions of these results are discussed . 


Summary: Sample size methods and programs for reliability studies are developed. The two way balanced analysis of variance model without interaction is the focus. The sample size guarantees a user specified mean confidence interval width. Modified large sample and generalized confidence interval methods are used. Novel computational algorithms are developed studied and implemented.
A Quasi Extended Chebyshev space is a space of sufficiently differentiable functions in which any Hermite interpolation problem which is not a Taylor problem is unisolvent . On a given interval the class of all spaces which contains constants and for which the space obtained by differentiation is a QEC space has been identified as the largest class of spaces which can be used for design . As a first step towards determining the largest class of splines for design we consider a sequence of QEC spaces on adjacent intervals all of the same dimension we join them via connection matrices so as to maintain both the dimension and the unisolvence . The resulting space is called a Quasi Extended Chebyshev Piecewise space . We show that all QECP spaces are inverse images of two dimensional Chebyshev spaces under piecewise generalised derivatives associated with systems of piecewise weight functions . We show illustrations proving that QECP spaces can produce interesting shape effects . 


Summary: Introduce Quasi Extended Chebyshev piecewise spaces. Develop their properties for design e.g. existence pseudoaffinity of blossoms. Determine the class of all such spaces. Provide illustrations.
This study applied a simulation method to map the temperature distribution based on magnetic resonance imaging of individual patients and investigated the influence of different pelvic tissue types as well as the choice of thermal property parameters on the efficiency of endorectal cooling balloon . MR images of four subjects with different prostate sizes and pelvic tissue compositions including fatty tissue and venous plexus were analyzed . The MR images acquired using endorectal coil provided a realistic geometry of deformed prostate that resembled the anatomy in the presence of ECB . A single slice with the largest two dimensional cross sectional area of the prostate gland was selected for analysis . The rectal wall prostate gland peri rectal fatty tissue peri prostatic fatty tissue peri prostatic venous plexus and urinary bladder were manually segmented . Pennes bioheat thermal model was used to simulate the temperature distribution dynamics by using an in house finite element mesh based solver written in MATLAB . The results showed that prostate size and periprostatic venous plexus were two major factors affecting ECB cooling efficiency . For cases with negligible amount of venous plexus and small prostate the average temperature in the prostate and neurovascular bundles could be cooled down to 25 C within 30min . For cases with abundant venous plexus and large prostate the temperature could not reach 25 C at the end of 3h cooling . Large prostate made the cooling difficult to propagate through . The impact of fatty tissue on cooling effect was small . The filling of bladder with warm urine during the ECB cooling procedure did not affect the temperature in the prostate or NVB . In addition to the 2D simulation in one case a 3D pelvic model was constructed for volumetric simulation . It was found that the 2D slice with the largest cross sectional area of prostate had the most abundant venous plexus and was the most difficult slice to cool thus it may provide a conservative prediction of the cooling effect . This feasibility study demonstrated that the simulation tool could potentially be used for adjusting the setting of ECB for individual patients during hypothermic radical prostatectomy . Further studies using MR thermometry are required to validate the in silico results obtained using simulation . 


Summary: This study investigated the influence of different pelvic tissue types as well as the choice of thermal property parameters on the efficacy of endorectal cooling balloon ECB . Prostate size and periprostatic venous plexus were two major factors affecting ECB cooling efficiency. Large prostate made the cooling difficult to propagate through the prostate. Patients with abundant periprostatic venous plexus required a longer time for neurovascular bundle NVB cooling. This feasibility study demonstrated that the simulation tool could potentially be used for adjusting the setting of ECB for hypothermic radical prostatectomy.
Using ab initio calculations we demonstrate that extra electrons in pure amorphous SiO2 can be trapped in deep band gap states . Classical potentials were used to generate amorphous silica models and density functional theory to characterise the geometrical and electronic structures of trapped electrons . Extra electrons can trap spontaneously on pre existing structural precursors in amorphous SiO2 and produce 3.2eV deep states in the band gap . These precursors comprise wide O Si O angles and elongated Si O bonds at the tails of corresponding distributions . The electron trapping in amorphous silica structure results in an opening of the O Si O angle . We estimate the concentration of these electron trapping sites to be 10 19 cm 


Summary: Wide O Si O angles in bulk amorphous silica are shown to trap electrons. Trapped electron levels appear 3.2eV below the bottom of the silica conduction band. Estimated concentration of electron trapping sites is 5 1019.
Background and objective Patients who visit emergency department may have symptoms of occult cancers . Methods We studied a random cohort of one million subjects from Taiwan National Health Insurance Research Database between 2000 and 2008 to evaluate the ED utilization of individuals who were subsequently diagnosed with digestive tract cancers . The case group was digestive tract cancer patients and the control group was traumatic fracture patients . We reviewed record of ED visits only from 4 to 15 months before the cancer diagnoses . Results There were 2635 and 6665 in the case and control groups respectively . Patients adjusted odds ratio with 95 confidence interval for the case group were 1.36 for Abdominal ultrasound 2.16 pan endoscopy 1.72 guaiac fecal occult blood test 1.42 plain abdominal X rays 1.20 SGOT 1.27 SGPT 1.66 total bilirubin 2.41 direct bilirubin 1.21 hemoglobin and 3.63 blood transfusion respectively . Blood transfusion in the ED was a significant predictor of the individual subsequently diagnosed with digestive tract cancer . Conclusions The health system could identify high risk patients early by real time review of their ED utilization before the diagnosis of digestive tract cancers . We proposed a follow up methodology for daily screening of patients with high risk of digestive tract cancer by informatics system in the ED . 


Summary: It is the first population based study to identify patients whose ED visits prior to diagnosis of digestive tract cancer. Certain examinations and blood transfusion in ED from 4 to 15 months prior to diagnosis was the significant predictors. We proposed a screening method of potential patients with digestive tract cancer by clinical decision support system in ED. Implementation of informatics system in ED can provide an opportunity for early detection of occult digestive tract cancer.
There are various medical image sharing and electronic whiteboard systems available for diagnosis and discussion purposes . However most of these systems ask clients to install special software tools or web plug ins to support whiteboard discussion special medical image format and customized decoding algorithm of data transmission of HRIs . This limits the accessibility of the software running on different devices and operating systems . In this paper we propose a solution based on pure web pages for medical HRIs lossless sharing and e whiteboard discussion and have set up a medical HRI sharing and e whiteboard system which has four layered design HRIs access layer we improved an tile pyramid model named unbalanced ratio pyramid structure to rapidly share lossless HRIs and to adapt to the reading habits of users format conversion layer we designed a format conversion engine on server side to real time convert and cache DICOM tiles which clients requesting with window level parameters to make browsers compatible and keep response efficiency to server client business logic layer we built a XML behavior relationship storage structure to store and share users behavior to keep real time co browsing and discussion between clients web user interface layer AJAX technology and Raphael toolkit were used to combine HTML and JavaScript to build client RIA to meet clients desktop like interaction on any pure webpage . This system can be used to quickly browse lossless HRIs and support discussing and co browsing smoothly on any web browser in a diversified network environment . The proposal methods can provide a way to share HRIs safely and may be used in the field of regional health telemedicine and remote education at a low cost . 


Summary: Designed methods for medical HRIs rapid accessing presentation and discussion on pure web browsers. Improved a tile pyramid to adapt to the reading habits of users for HRIs accessing. Built a format conversion engine FCE to make DICOM browsing compatibility and response efficiency. Designed a XML behavior relationship to store and share users behavior to keep online discussion. Created a HRIs sharing and electronic whiteboard system in a diversified network environment.
Breast cancer is one of the most perilous diseases among women . Breast screening is a method of detecting breast cancer at a very early stage which can reduce the mortality rate . Mammography is a standard method for the early diagnosis of breast cancer . In this paper a new algorithm is proposed for breast cancer detection and classification in digital mammography based on Non Subsampled Contourlet Transform and Super Resolution . The presented algorithm includes three main parts including pre processing feature extraction and classification . In the pre processing stage after determining the region of interest by an automatic technique the quality of image is improved using NSCT and SR algorithm . In the feature extraction part several features of the image components are extracted and skewness of each feature is calculated . Finally AdaBoost algorithm is used to classify and determine the probability of benign and malign disease . The obtained results on Mammographic Image Analysis Society database indicate the significant performance and superiority of the proposed method in comparison with the state of the art approaches . According to the obtained results the proposed technique achieves 91.43 and 6.42 as a mean accuracy and FPR respectively . 


Summary: We propose a new algorithm for breast cancer detection and classification. Our system can accurately detect the probability of benign or malign breast lesion. We utilize NSCT transform and super resolution to improve the quality of the images. The results on MIAS database show significant performance of the proposed method. Our system achieves 91.43 and 6.42 as a mean accuracy and FPR respectively.
Patients use nurse call systems to signal nurses for medical help . Traditional push button flashing lamp call systems are not integrated with other hospital automation systems . Therefore nurse response time becomes a matter of personal discretion . The improvement obtained by integrating a pager system into the nurse call systems does not increase care efficiency because unnecessary visits are still not eliminated . To obtain an immediate response and a purposeful visit by a nurse regardless of the location of nurse in hospital traditional systems have to be improved by intelligent telephone system integration . The results of the developed Nurse Call System Software the Wireless Phone System Software the Location System Software and the communication protocol are provided together with detailed XML message structures . The benefits of the proposed system are also discussed and the direction of future work is presented . 


Summary: Current nurse call systems fail to transfer a nurse call to the next available nurse if the primary nurse is on the phone with another patient. Current nurse call systems fail to transfer a nurse call to the next available nurse if the primary nurse is currently on another visit. Our contribution Both the nurse and the patient know that if the primary nurse is not available the system will dedicate the next available nurse. Our contribution The patient knows that his her call is guaranteed to be processed by the hospital. Our contribution The patient can reach a nurse equipped with a mobile DECT phone quicker.