Miracle-dz/UniFAR-FTUs huggingface dataset:
Diagnosability of Synthetic Retinal Fundus Images for Plus Disease Detection in Retinopathy of Prematurity

Advances in generative adversarial networks have allowed for engineering of highly-realistic images. Many studies have applied these techniques to medical images. However, evaluation of generated medical images often relies upon image quality and reconstruction metrics, and subjective evaluation by laypersons. This is acceptable for generation of images depicting everyday objects, but not for medical images, where there may be subtle features experts rely upon for diagnosis. We implemented the pix2pix generative adversarial network for retinal fundus image generation, and evaluated the ability of experts to identify generated images as such and to form accurate diagnoses of plus disease in retinopathy of prematurity. We found that, while experts could discern between real and generated images, the diagnoses between image sets were similar. By directly evaluating and confirming physicians' abilities to diagnose generated retinal fundus images, this work supports conclusions that generated images may be viable for dataset augmentation and physician training.
A Vital Signs Telemonitoring Programme Improves the Dynamic Prediction of Readmission Risk in Patients with Heart Failure

Heart failure (HF) is a leading cause of hospital readmissions. There is great interest in approaches to efficiently predict emerging HF-readmissions in the community setting. We investigate the possibility of leveraging streaming telemonitored vital signs data alongside readily accessible patient profile information for predicting evolving 30-day HF-related readmission risk. We acquired data within a non-randomized controlled study that enrolled 150 HF patients over a 1-year post-discharge telemonitoring and telesupport programme. Using the sequential data and associated ground truth readmission outcomes, we developed a recurrent neural network model for dynamic risk prediction. The model detects emerging readmissions with sensitivity > 71%, specificity > 75%, AUROC ~80%. We characterize model performance in relation to telesupport based nurse assessments, and demonstrate strong sensitivity improvements. Our approach enables early stratification of high-risk patients and could enable adaptive targeting of care resources for managing patients with the most urgent needs at any given time.
The Effect of Hemodialysis Treatment on Ventricular Arrhythmogenesis Parameters in Electrocardiography

Amac: Hemodiyaliz (HD) hastalarinda ventrikuler aritmiler ve ani kardiyak olum (AKO) dahil kardiyovaskuler olaylar birincil olum kaynagidir. QT araligi, QT dispersiyonu (QTd), TPe araligi, TPe / QT orani ve kardiyak-elektrofizyolojik denge (iCEB = QT / QRS) gibi EKG parametrelerinin kontrol edilmesi, yuksek aritmi ve SCD riski olan hastalarin siniflandirilmasinda yararli olabilir. Calismamiz, HD seansi oncesi ve sonrasinda elektrokardiyografik parametrelerdeki degisimi saglikli kontrol grubu ile karsilastirmayi amacladi. Yontemler: Calismaya 49 HD hastasi ve 50 saglikli gonullu dahil edildi. Gruplar hemodiyaliz ve kontrol grubu olarak iki gruba ayrildi. Hemodiyaliz grubunun EKG'leri diyaliz oncesi ve sonrasi degerlendirildi. EKG verileri tarandi ve dijital bir platformda degerlendirildi. QT, cQT, QTd, TPe, TPe / QT, TPe / cQT, QT / QRS ve cQT / QRS olculdu. Bulgular: Hemodiyaliz sonrasi QTd, cQTd, TPe, TPe / QTc ve QRS pre-HD'ye gore anlamli olarak azalirken (her biri icin p <0,05), diyaliz tedavisi sonrasi HR, iCEB ve iCEBc anlamli artis gosterdi (p <0,05 icin her biri). Diyaliz oncesi EKG parametreleri ile kontrol grubu karsilastirildiginda QT, cQT, QTd, cQTd, TPe ve iCEBc pre-HD'de anlamli olarak daha yuksekti (her biri icin p <0.05). Diyaliz sonrasi EKG parametreleri karsilastirildiginda, HR, cQT, QTd, cQTd, iCEB ve iCEBc degerleri kontrol grubuna gore anlamli olarak yuksekti (her biri icin p <0.05). Sonuc: HD hastalarinda ventrikuler repolarizasyon ve depolarizasyonu birlikte gosteren elektrokardiyografik parametreler degerlendirilerek aritmi ve ani kardiyak olum riski ongorulebilir.
The Roles of Reduced Folate Carrier-1 (RFC1) A80G (rs1051266) Polymorphism in Congenital Heart Disease: A Meta-Analysis

Background We performed the present study to better elucidate the correlation of reduced folate carrier-1 (RFC1) A80G (rs1051266) polymorphism with the risk of congenital heart disease (CHD). Material/Methods According to the designed search strategy, a systematic literature search was performed through the PubMed, Cochrane Library, Web of Science, EMBASE, CNKI, VIP, and Wan Fang databases to collect published case-control studies on the correlation between RFC1 A80G polymorphism and CHD. All relevant studies up to October 1, 2019 were identified. The odds ratio (OR) and 95% confidence interval (CI) of the genotype distribution were used as the effect indicators. Results A total of 6 eligible studies was finally included in our meta-analysis, including 724 children with CHD, 760 healthy children, 258 mothers of the children with CHD, and 334 mothers of healthy control children. The meta-analysis revealed that for fetal analysis, only in the heterozygous model (GA vs GG, OR=1.36, 95% CI [1.06, 1.75], P=0.02) was RFC1 A80G polymorphism associated with risk of CHD. In maternal analysis, 3 genetic models of RFC1 A80G polymorphism increased the risk of CHD: the allelic model (A vs G, OR=1.36, 95% CI [1.07, 1.71], P=0.01), the homozygote model (AA vs GG, OR=2.99, 95%CI [1.06, 8.41], P=0.04), and the dominance model (GA+AA vs GG, OR=1.53, 95%CI [1.08, 2.16], P=0.02). Conclusions The maternal RFC1 A80G polymorphism has a strong correlation with CHD. Compared with the G allele, the A allele increases the risk of CHD by 0.36-fold.
Bleeding Entity Recognition in Electronic Health Records: A Comprehensive Analysis of End-to-End Systems

A bleeding event is a common adverse drug reaction amongst patients on anticoagulation and factors critically into a clinician's decision to prescribe or continue anticoagulation for atrial fibrillation. However, bleeding events are not uniformly captured in the administrative data of electronic health records (EHR). As manual review is prohibitively expensive, we investigate the effectiveness of various natural language processing (NLP) methods for automatic extraction of bleeding events. Using our expert-annotated 1,079 de-identified EHR notes, we evaluated state-of-the-art NLP models such as biLSTM-CRF with language modeling, and different BERT variants for six entity types. On our dataset, the biLSTM-CRF surpassed other models resulting in a macro F1-score of 0.75 whereas the performance difference is negligible for sentence and document-level predictions with the best macro F1-scores of 0.84 and 0.96, respectively. Our error analyses suggest that the models' incorrect predictions can be attributed to variability in entity spans, memorization, and missing negation signals.
Biological activities and phytochemical screening of (Thunb.) DC. Leaves and Stem barks Extracts

From reports obesity, anti were therefore analyzed for its biological activities. The antibacterial activities of Gram positive and gram negative bacteria using agar well diffusion method. The analysis for the phytochemical contents, antioxidant and anti barks were determined using sta The leaves and stem barks extracts of only the aqueous leaf extract. mg/ml. (65.44 mg/g) and saponins (68.21 mg/g) were significantly higher in the aqueous leaf extract while phenols (94.13 mg/g) conten scavenging activity using ABTS, FRAP and DPPH showed that the extracts possess good free radical scavenging activities with different free radical species that is comparable with ascorbic acid and anti These findings support the folkloric usage of be used to manage diseases caused by the teste flavonoids, anti anti
An Extensive Analysis of the Vision-based Deep Learning Techniques for Action Recognition

Action recognition involves the idea of localizing and classifying actions in a video over a sequence of frames. It can be thought of as an image classification task extended temporally. The information obtained over the multitude of frames is aggregated to comprehend the action classification output. Applications of action recognition systems range from assistance for healthcare systems to human-machine interaction. Action recognition has proven to be a challenging task as it poses many impediments including high computation cost, capturing extended context, designing complex architectures, and lack of benchmark datasets. Increasing the efficiency of algorithms in human action recognition can significantly improve the probability of implementing it in real-world scenarios. This paper has summarized the evolution of various action localization, classification, and detection algorithms applied to data from vision-based sensors. We have also reviewed the datasets that have been used for the action classification, localization, and detection process. We have further explored the areas of action classification, temporal and spatiotemporal action detection, which use convolution neural networks, recurrent neural networks, or a combination of both. Keywords—Action recognition; deep learning; vision sensors; convolution neural networks (CNN); recurrent neural networks (RNN); action classification; temporal action detection; spatiotemporal action detection
Corporate Social Responsibility And Profitability Of Nigerian Banks: Implications For Service Delivery

This paper sought to establish the relationship between corporate social responsibility (CSR) and profitability of Nigerian banks; as well as its implications for service delivery (SD). Corporate philanthropy was used as the only dimension of CSR; while profit after tax (PAT) was used to measure profitability. Using data from annual reports of five topmost banks in Nigeria (FBN, Zenith Bank, GTbank, UBA and Access bank); and the ordinary least square regression technique for data analysis, it was found that there is positive and significant relationship between CSR and Profitability; with far-reaching implications for SD. Based on this, it was concluded that banks in Nigeria can improve their profitability and SD through improved CSR practices. The study recommended that banks should view CSR as a means of achieving some corporate objectives such that CSR practices should be properly integrated into their operations; they should not limit their CSR practices to corporate philanthropy alone; regulatory bodies should be empowered to maintain international standards; they should develop proper framework for implementation of CSR programmes so as to execute programmes that have direct bearing on the needs of the people.
MONITORING AND CONTROL OVER MANAGERIAL DECISION-MAKING IN GOVERNMENT AUTHORITIES

The present academic paper considers the current problem of improving the efficiency of managerial decision-making in government authorities through the use of rational tools for monitoring and control. The welfare of society and the level the country’s development depend on these decisions, and control is an effective means of influencing the system of public administration. The purpose of the study is to systematize and harmonize the methodological provisions of monitoring and control of public administration, which are implemented through the process of managerial decision-making. Dialectical and logical methods, methods of analysis and synthesis, comparison and classification, as well as the matrix method have been used in the academic paper. As a result of the research conducted, the methodical provisions of monitoring and control of government authorities have been systematized, in particular, Yana V. Zoska, Dеnys S. Martyshyn, Nataliya V. Zaiats, Dmytro Yu. Arabadzhyiev and Svitlana V. Kapitanets http://www.iaeme.com/IJM/index.asp 370 editor@iaeme.com the classification of types and methods of control has been carried out, the purposes and directions of monitoring have been generalized. The approach to structuring the control of decisions of government authorities has been improved by highlighting the subject of control (control by goals and criteria, comparison with the standard, control of the absence of violations and compliance with the procedure). The control tools have been systematized and coordinated with the stages of development and managerial decision-making, which will improve the efficiency of government control in the process of implementing the functions of state and municipal governance.
IJSRD-International Journal for Scientific Research & Development| Vol. 5, Issue 05, 2017 | ISSN (online): 2321-0613

In This research, we evaluate the energy consumption and storage requirement for the baseline scheme using the proposed models for the health monitoring devices. Since each sensor has its own sampling rate and resolution, its energy consumption differs from that of others. They correspond to the minimum and maximum sampling rates, respectively. The minimum/maximum battery lifetimes are reported assuming that each sensor node uses a regular coin cell battery (CR2032). A regular coin cell battery is commonly used in biomedical sensor. Not surprisingly, ECG and EEG sensors are seen to consume the most amount of energy. Thus, these sensors are the main obstacles to providing long-term health monitoring.
Exploring the Efﬁciency of Bioinformatics Applications with CPUs, Integrated GPUs and Processing-in-Memory

—Bioinformatics applications on the area of genomics deal with large quantities of data on genetic information of groups of individuals. These applications are important to help biologists identify interacting groups of Single Nucleotide Polymorphisms responsible for diseases in humans, among other uses. This work will explore the algorithms used in this class of applications and adapt them to run in platforms with different processing technologies, CPU, Integrated GPU and Processing-in-Memory, in order to deeply evaluate their capabilities to deliver the maximum performance and energy efﬁciency. The work developed will aim to ﬁnd the performance and energy efﬁciency gains obtained by using each processing technology, and provide insight on the use of alternate technologies for memory-intensive applications in the ﬁeld of bioinformatics.
Easy Medication Reconciliation at Hospital Admission: The EzMedRec Decision Support System

Medication reconciliation (MR) aims at preventing medication errors at care transitions. It is a complex, time-consuming, cognitively demanding pharmacological task. We have developed a decision support system, EzMedRec, to assist retroactive MR at hospital admission. EzMedRec compares the best possible medication history (BPMH), i.e., all medications taken by the patient before hospitalization, to the list of admission medication orders (AMO). The process includes (i) the decomposition of BPMH and AMO drugs into their active ingredients (AIs), (ii) the detection of medication discontinuations and additions, and (iii) the identification of modified medication orders. The ATC classification is used to semantically enrich MR by comparing discontinued AIs and added AIs and suggesting a potential intentional drug substitution serving the same therapeutic objective. EzMedRec has been evaluated on a sample of 52 actual MRs involving 822 medication order lines, 406 in BPMHs, and 416 in AMOs with a global accuracy of 98,3%.
Comparative Study of Various Approaches for Ensemble-based De-identification of Electronic Health Record Narratives

De-identification of electric health record narratives is a fundamental task applying natural language processing to better protect patient information privacy. We explore different types of ensemble learning methods to improve clinical text de-identification. We present two ensemble-based approaches for combining multiple predictive models. The first method selects an optimal subset of de-identification models by greedy exclusion. This ensemble pruning allows one to save computational time or physical resources while achieving similar or better performance than the ensemble of all members. The second method uses a sequence of words to train a sequential model. For this sequence labelling-based stacked ensemble, we employ search-based structured prediction and bidirectional long short-term memory algorithms. We create ensembles consisting of de-identification models trained on two clinical text corpora. Experimental results show that our ensemble systems can effectively integrate predictions from individual models and offer better generalization across two different corpora.
Position Estimation Of UAV By Image Processing With Neural Networks

Abstract – This paper presents a study of three artificial neural networks with supervised training and different architectures: network with radial basis function, multilayer perceptron and cellular neural network. These networks were applied to edge detection in aerial and satellite images, for later correlation calculation in spatial domain between these images to simulate the estimation of the geographical position of a unmanned aerial vehicle UAV. The neural networks results were compared with Sobel and Canny operators.
Assessment of Lower Limb Load Distribution in Patients Treated with the Ilizarov Method for Tibial Nonunion

Background Successful treatment of tibial nonunion should lead to a complete bone union, lack of pain, and pathological mobility of the lower extremity, as well as to the achievement of satisfactory joint mobility and muscle strength, which in turn improves its biomechanics. The objective of this study was to assess the load placed on the lower limbs in patients subjected to treatment with the Ilizarov method due to aseptic tibial nonunion. Material/Methods This research involved 24 participants (average age, 55 years). All were diagnosed with aseptic tibia nonunion and treated with the Ilizarov external fixator between 2000 and 2017. The control group was matched to the treated group in terms of sex and age. This study used pedobarography evaluation to assess lower limb load distribution. Results No differences were found in the distribution of the load over the entire foot or of the forefoot and hindfoot of the treated limb in comparison to the non-dominant limb of the controls, or in the healthy limb of the treated group compared to the dominant limb of the control group. Similarly, differences in load distribution between the operated and healthy limbs of the treated group were insignificant. Conclusions Patients subjected to treatment with the Ilizarov external fixator for aseptic tibial nonunion show symmetrical load distribution on both lower limbs following treatment, which does not differentiate them in this respect from healthy individuals. Treated patients presented with a symmetrical distribution of the load on the lower extremities over the entire foot surface, including the forefoot and hindfoot. Finally, the Ilizarov external fixator enables restoration of correct static biomechanics of the treated limbs over the period of aseptic tibial nonunion therapy.
Employees’ Turnover Intention Of Mice Industry In Jakarta Indonesia

This study aims to analyze the effects of workload, the empowerment of employees towards job satisfaction and job stress and its impacts on the Turnover Intentions of the Employees of MICE industry. When this study was conducted, the number of respondents were 213 people which was eligible in MICE industry in as many as 71 companies which already have certified their employeesat the Institute Professional Certification (LSP MICE). The locations of the companies are widespread in Jabodetabek (Jakarta, Bogor, Tangerang, Bekasi), Indonesia. Data analysis uses the Structural Equation Model (SEM) with LISREL software. The results of the study showed that the workload has no significant effects on the intention to move out, job satisfaction and work stress of the employees. The empowerment of employees has a direct effect on job satisfaction and work stress. Meanwhile, the empowerment of the employees has no direct effect on the intention to move out but has an indirect effect through variables of the employee’s job satisfaction. This is because the employee’s job satisfaction has a direct effect on the intention to move out. Whereas the work stress does not affect work satisfaction or the intention of the employees to change jobs. Keyword: MICE, employees and Industry -------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 22-06-2019 Date of acceptance: 05-07-2019 -------------------------------------------------------------------------------------------------------------------------------------------------
Plasticity in structural and functional traits associated with photosynthesis in Fimbristylis complanata (Retz.) Link. under salt stress

Fimbristylis complanata (Retz.) Link. is a halophytic sedge and commonly found in salt-affected wetlands and salt marshes. This species is less explored, particularly no information available on salinity tolerance in the literature. In the present work, structural and functional modifications of photosynthesis in F. complanata were evaluated under salt stress. A complete randomized design with three replications and three salt regimes (0, 200 and 400 mM NaCl) were maintained throughout the experiment. Population SH collected from the highest saline habitat (ECe 49.28 dS m) ranked as the highest tolerant, which showed an increase in biomass and chlorophyll pigments under salt stress. Modification in gas exchange parameters include decline in transpiration rate (E), while increase water use efficiency (WUE) and net CO2 assimilation rate (Pn), while structural modifications in SH population include increase in leaf succulence, cortical region thickness, bulliform thickness, aerenchyma formation, metaxylem and phloem area. Moderately saline population KM (ECe 29.56 dS m) exhibited significant alterations, like E (transiently up to 200 mM NaCl) and maintence of Pn up to 400 mM. This population altered leaf structural and epidermal traits related to photosynthetic efficiency. Least saline population LR (ECe 21.49 dS m) accumulates high chlorophyll content, increased leaf succulence and secured higher abaxial stomatal density. Present results suggest that F. complanata could proficiently maintain photosynthesis by several structural and functional modifications.
Human Computer Interaction and Eye Tracking Eye Mouse

Abstrac t — this paper intends to use eye gazing techniques to allow a user to move the mouse pointer using his/her eyes. This objective was achieved using a trained Haar classifier for the face and eyes Detection. The final system is able to detect successfully where the user is looking and to track the eye's gaze. Results illustrating this functionality are well documented in this paper. Although that, some limitations in the movement scaling to fit to the screen dimensions - must be eliminated in future.