Search results for: delivery of disease data information

Authors: Duhania O. Mahara, Santi W. Purnami, Aulia N. Fitria, Merissa N. Z. Wirontono, Revina Musfiroh, Shofi Andari, Sagiran Sagiran, Estiana Khoirunnisa, Wahyudi Widada

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For assessing interventions in numerous disease areas, the use of multiple time-to-event outcomes is common. An individual might experience two different events called bivariate time-to-event data, the events may be correlated because it come from the same subject and also influenced by individual characteristics. The bivariate time-to-event case can be applied by copula-based bivariate Cox survival model, using the Clayton and Frank copulas to analyze the dependence structure of each event and also the covariates effect. By applying this method to modeling the recurrent event infection of hemodialysis insertion on chronic kidney disease (CKD) patients, from the AIC and BIC values we find that the Clayton copula model was the best model with Kendall’s Tau is (τ=0,02).

Keywords: bivariate cox, bivariate event, copula function, survival copula

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Authors: Fernando L. P. Santos, Luiz G. Lyra, Helenice O. Florentino, Daniela R. Cantane

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Dengue is a febrile infectious disease caused by a virus of the family Flaviridae. It is transmitted by the bite of mosquitoes, usually of the genus Aedes aegypti. It occurs in tropical and subtropical areas of the world. This disease has been a major public health problem worldwide, especially in tropical countries such as Brazil, and its incidence has increased in recent years. Dengue is a subject of intense research. Efficient forms of mosquito control must be considered. In this work, the mono-objective optimal control problem was solved for analysing the dengue disease problem. Chemical and biological controls were considered in the mathematical aspect. This model describes the dynamics of mosquitoes in water and winged phases. We applied the genetic algorithms (GA) to obtain optimal strategies for the control of dengue. Numerical simulations have been performed to verify the versatility and the applicability of this algorithm. On the basis of the present results we may recommend the GA to solve optimal control problem with a large region of feasibility.

Keywords: genetic algorithm, dengue, Aedes aegypti, biological control, chemical control

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Authors: Philipp Ruf, Massiwa Chabbi, Christoph Reich, Djaffar Ould-Abdeslam

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In recent years, convolutional neural networks (CNN) have demonstrated high performance in image analysis, but oftentimes, there is only structured data available regarding a specific problem. By interpreting structured data as images, CNNs can effectively learn and extract valuable insights from tabular data, leading to improved predictive accuracy and uncovering hidden patterns that may not be apparent in traditional structured data analysis. In applying a single neural network for analyzing multimodal data, e.g., both structured and unstructured information, significant advantages in terms of time complexity and energy efficiency can be achieved. Converting structured data into images and merging them with existing visual material offers a promising solution for applying CNN in multimodal datasets, as they often occur in a medical context. By employing suitable preprocessing techniques, structured data is transformed into image representations, where the respective features are expressed as different formations of colors and shapes. In an additional step, these representations are fused with existing images to incorporate both types of information. This final image is finally analyzed using a CNN.

Keywords: CNN, image processing, tabular data, mixed dataset, data transformation, multimodal fusion

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Authors: Poramatdha Chutimant

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The objective of the research was to propose a model of teacher leadership in history instruction for utilization. Everett M. Rogers’ Diffusion of Innovations Theory is applied as theoretical framework. Qualitative method is to be used in the study, and the interview protocol used as an instrument to collect primary data from best practices who awarded by Office of National Education Commission (ONEC). Open-end questions will be used in interview protocol in order to gather the various data. Then, information according to international context of history instruction is the secondary data used to support in the summarizing process (Content Analysis). Dendrogram is a key to interpret and synthesize the primary data. Thus, secondary data comes as the supportive issue in explanation and elaboration. In-depth interview is to be used to collected information from seven experts in educational field. The focal point is to validate a draft model in term of future utilization finally.

Keywords: history study, nationalism, patriotism, responsible citizenship, teacher leadership

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Authors: Yasmeen A. S. Essawy, Khaled Nassar

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With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.

Keywords: building information modeling (BIM), elemental graph data model (EGDM), geometric and topological data models, graph theory

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Authors: Ahmed Fradi

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In a digital world in perpetual evolution and acceleration, data more and more voluminous, rich and varied, the new software solutions emerged with the Big Data phenomenon offer new opportunities to the company enabling it not only to optimize its business and to evolve its production model, but also to reorganize itself to increase competitiveness and to identify new strategic axes. Design and manufacturing industrial companies, like the others, face these challenges, data represent a major asset, provided that they know how to capture, refine, combine and analyze them. The objective of our paper is to propose a solution allowing geometric and topological information extraction from 3D CAD model (precisely STEP files) databases, with specific algorithm based on the programming paradigm MapReduce. Our proposal is the first step of our future approach to 3D CAD object retrieval.

Keywords: Big Data, MapReduce, 3D object retrieval, CAD, STEP format

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Authors: Ana Corberan-Vallet, Karen C. Florez, Ingrid C. Marino, Jose D. Bermudez

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In 2016, the Region of the Americas was declared free of measles, a viral disease that can cause severe health problems. However, since 2017, measles has reemerged in Venezuela and has subsequently reached neighboring countries. In 2018, twelve American countries reported confirmed cases of measles. Governmental and health authorities in Colombia, a country that shares the longest land boundary with Venezuela, are aware of the need for a strong response to restrict the expanse of the epidemic. In this work, we apply a Bayesian hierarchical Poisson model with an underlying cluster structure to describe disease incidence in Colombia. Concretely, the proposed methodology provides relative risk estimates at the department level and identifies clusters of disease, which facilitates the implementation of targeted public health interventions. Socio-demographic factors, such as the percentage of migrants, gross domestic product, and entry routes, are included in the model to better describe the incidence of disease. Since the model does not impose any spatial correlation at any level of the model hierarchy, it avoids the spatial confounding problem and provides a suitable framework to estimate the fixed-effect coefficients associated with spatially-structured covariates.

Keywords: Bayesian analysis, cluster identification, disease mapping, risk estimation

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Authors: Pradeep Kumar, Shibashish Chakraborty, Sasadhar Bera

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In the anticipation of demand fluctuations, services cannot be inventoried and hence it creates a difficult problem in marketing of services. The inability to meet customers (patients) requirements in healthcare context has more serious consequences than other service sectors. In order to meet patient requirements in the current uncertain environment, healthcare organizations are seeking ways for improved service delivery. Flexibility provides a mechanism for reducing variability in service encounters and improved performance. Flexibility is defined as the ability of the organization to cope with changing circumstances or instability caused by the environment. Patient satisfaction is an important performance outcome of healthcare organizations. However, the paucity of information exists in healthcare delivery context to examine the impact of flexibility on patient satisfaction and behavioral intention. The present study is an attempt to develop a conceptual foundation for investigating overall impact of flexibility on patient satisfaction and behavioral intention. Several dimensions of flexibility in healthcare context are examined and proposed to have a significant impact on patient satisfaction and intention. Furthermore, the study involves a critical examination of determinants of patient satisfaction and development of a comprehensive view the relationship between flexibility, patient satisfaction and behavioral intention. Finally, theoretical contributions and implications for healthcare professionals are suggested from flexibility perspective.

Keywords: healthcare, flexibility, patient satisfaction, behavioral intention

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Authors: Wiseman Emmanuel Nkhomah, Chiyembekezo Kachimanga, Moses Banda Aron, Julia Higgins, Manuel Mulwafu, Kondwani Mpinga, Mwayi Chunga, Grace Momba, Enock Ndarama, Dickson Sumphi, Atupere Phiri, Fabien Munyaneza

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Background: Data is key to supporting health service delivery as stakeholders, including NGOs rely on it for effective service delivery, decision-making, and system strengthening. Several studies generated debate on data quality from national health management information systems (HMIS) in sub-Saharan Africa. This limits the utilization of data in resource-limited settings, which already struggle to meet standards set by the World Health Organization (WHO). We aimed to evaluate data quality improvement of Neno district HMIS over a 4-year period (2018 – 2021) following quarterly data reviews introduced in January 2020 by the district health management team and Partners In Health. Methods: Exploratory Mixed Research was used to examine report rates, followed by in-depth interviews using Key Informant Interviews (KIIs) and Focus Group Discussions (FGDs). We used the WHO module desk review to assess the quality of HMIS data in the Neno district captured from 2018 to 2021. The metrics assessed included the completeness and timeliness of 34 reports. Completeness was measured as a percentage of non-missing reports. Timeliness was measured as the span between data inputs and expected outputs meeting needs. We computed T-Test and recorded P-values, summaries, and percentage changes using R and Excel 2016. We analyzed demographics for key informant interviews in Power BI. We developed themes from 7 FGDs and 11 KIIs using Dedoose software, from which we picked perceptions of healthcare workers, interventions implemented, and improvement suggestions. The study was reviewed and approved by Malawi National Health Science Research Committee (IRB: 22/02/2866). Results: Overall, the average reporting completeness rate was 83.4% (before) and 98.1% (after), while timeliness was 68.1% and 76.4 respectively. Completeness of reports increased over time: 2018, 78.8%; 2019, 88%; 2020, 96.3% and 2021, 99.9% (p< 0.004). The trend for timeliness has been declining except in 2021, where it improved: 2018, 68.4%; 2019, 68.3%; 2020, 67.1% and 2021, 81% (p< 0.279). Comparing 2021 reporting rates to the mean of three preceding years, both completeness increased from 88% to 99% (in 2021), while timeliness increased from 68% to 81%. Sixty-five percent of reports have maintained meeting a national standard of 90%+ in completeness while only 24% in timeliness. Thirty-two percent of reports met the national standard. Only 9% improved on both completeness and timeliness, and these are; cervical cancer, nutrition care support and treatment, and youth-friendly health services reports. 50% of reports did not improve to standard in timeliness, and only one did not in completeness. On the other hand, factors associated with improvement included improved communications and reminders using internal communication, data quality assessments, checks, and reviews. Decentralizing data entry at the facility level was suggested to improve timeliness. Conclusion: Findings suggest that data quality in HMIS for the district has improved following collaborative efforts. We recommend maintaining such initiatives to identify remaining quality gaps and that results be shared publicly to support increased use of data. These results can inform Ministry of Health and its partners on some interventions and advise initiatives for improving its quality.

Keywords: data quality, data utilization, HMIS, collaboration, completeness, timeliness, decision-making

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Authors: R. K. Pateriya, Jyoti Bharti

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This paper presents an approach for data hiding methods which provides a secret communication between sender and receiver. The data is hidden in gray-scale images and the boundary of gray-scale image is used to store the mapping information. In this an approach data is in ASCII format and the mapping is in between ASCII value of hidden message and pixel value of cover image, since pixel value of an image as well as ASCII value is in range of 0 to 255 and this mapping information is occupying only 1 bit per character of hidden message as compared to 8 bit per character thus maintaining good quality of stego image.

Keywords: ASCII value, cover image, PSNR, pixel value, stego image, secret message

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Authors: Walid Al-Qerem, Ruba Zumot

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Background: The rise of obesity among children and adolescents remains a primary challenge for healthcare providers globally and in the Middle East. The aim of the present study is to determine the prevalence of obesity among 5-20 years old Jordanians based on CDC criteria. Method: A total of 5722 Jordanians (37% males; 63% females) aged 5-20 years data were retrieved from the Jordanian Ministry of Health electronic database (Hakeem). As per the CDC selection criteria, the chosen data pertains exclusively to healthy Jordanian children and adolescents who are medically sound, not suffering from health conditions, and not undergoing any treatments that could hinder normal growth patterns, such as severe infection, chronic kidney disease (CKD), Down’s syndrome, attention deficit hyperactivity disorder, cancer, heart disease, lung disease, cystic fibrosis, Crohn’s disease, type 1 diabetes, hormonal disturbances, any stress-related conditions, hormonal therapy such as corticosteroids, Growth hormones (GHS) or gonadotropin-releasing hormone agonists, insulin, and amphetamines or any other stimulants. In addition, participants with missing or invalid data values for anthropometric measurements were excluded from the study. Weight for age and body mass index for age were analyzed comparatively for Jordanian children and adolescents against the international growth standards. The Z-score for each record was computed based on CDC equations. As per CDC classifications, BMI for age percentiles, values ≥85th and < 95th are classified as overweight, and value at ≥ 95th is classified as obesity. Results: The average age of the evaluated sample was 12.33 ±4.39 years (10.79 ±3.39 for males and 13.23 ± 4.66 for females). The mean weight for males and females were 33.16±14.17 Kg and 133.54±17.17 cm for males, 43.86 ±18.82 Kg, and 142.19±18.35 for females, while for BMI the mean was for boys and girls 17.81±3.88 and 20.52±5.03 respectively. The results indicated that based on CDC criteria, 8.9% of males were classified as children/adolescents with overweight, and 9.7% were classified as children/adolescents with obesity, while in females, 17.8% were classified as children/adolescents with overweight and 10.2% were classified as children/adolescents with obesity. Discussion: The high prevalence of obesity reported in the present study emphasizes the importance of applying different strategies to prevent childhood obesity, including encouraging physical activity, promoting healthier food options, and behavioral changes. Conclusion: The results presented in this study indicated the high prevalence of overweight/obesity among Jordanian adolescents and children, which must be tagged by healthcare planners and providers.

Keywords: CDC, obesity, childhood, Jordan

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Authors: S. Yeo, M. Mathur

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Introduction: Obesity, defined as a Body Mass Index (BMI) of more than or equal to 30kg/m, is associated with an increased risk of complications during pregnancy and delivery. During labour, obese mothers often require greater intervention and have higher rates of caesarean section. Despite a low overall rate of serious complications following caesarean section, a high BMI predisposes to a higher risk of postoperative complications. Our study, therefore, aimed to investigate the impact of antenatal obesity on adverse outcomes following caesarean section, particularly wound-related infections. Materials and Methods: A retrospective cohort study of all caesarean deliveries during the first quarter of a chosen year was undertaken in our hospital, which is a tertiary referral centre with > 12,000 deliveries per year. Patients’ health records and data from our hospital’s electronic labour and delivery database were reviewed. Data analysis was performed using the Statistical Package for the Social Sciences (SPSS), and odds ratios plus adjusted odd ratios were calculated with 95% confidence intervals (CI). Results: A total of 1829 deliveries were reviewed during our study period. Of these, 180 (9.8%) patients were obese. The rate of caesarean delivery was 48.9% in obese patients versus 28.1% in non-obese patients. Post-operatively, 17% of obese patients experienced wound infection versus 0.2% of non-obese patients. Obese patients were also more likely to experience major postpartum haemorrhage (4.6% vs. 0.2%) and postpartum pyrexia (18.2% vs. 5.0%) in comparison to non-obese patients. Conclusions: Obesity is a significant risk factor in the development of postoperative complications following caesarean section. Wound infection remains a major concern for obese patients undergoing major surgery and results in extensive morbidity during the postnatal period. Postpartum infection can prolong recovery and affect maternal mental health, leading to reduced perinatal bonding with long-term implications on breastfeeding and parenting confidence. This study supports the need for the development of standardized protocols specifically for obese patients undergoing caesarean section. Multidisciplinary team care, in conjunction with anaesthesia, family physicians, and plastic surgery counterparts, early on in the antenatal journey, may be beneficial where wound complications are anticipated and to minimize the burden of postoperative infection in obese mothers.

Keywords: pregnancy, obesity, caesarean, infection

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Authors: M. Mydlárová Blaščáková, J. Bernasovská, J. Poráčová, I. Boroňová

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Obesity is frequent attendant phenomenon of patients with endocrinological disease. Between BMI and endocrinological diseases is close correlation. In thesis we focused on the allocation of hormone concentration – PTH and TSH, CHOL a mineral element Ca in a blood serum. The examined group was formed by 100 respondents (women) aged 36 – 83 years, who were divided into two groups – control group (CG), group with diagnosed endocrine disease (DED). The concentration of PTH and TSH, Ca and CHOL was measured through the medium of analyzers Cobas e411 (Japan); Cobas Integra 400 (Switzerland). At individuals was measured body weight as well as stature and thereupon from those data we enumerated BMI. On the basis of Student T-test in biochemical parameter of PTH and Ca we found out significantly meaningful difference (p<0,05) between CG and DED. In CG we made a founding the association between BMI and PTH by means of correlation analysis.

Keywords: biochemical markers, hormones, obesity, women

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Authors: Rania A. R. Soudan, Easter Joury

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Introduction: Psoriasis is a common chronic dermatologic disease. It may affect the mucous membranes. The presence of oral mucosal lesions has been a subject of controversy. The aim: To determine possible association between oral mucosal lesions and psoriasis, and to correlate the same with different types of psoriasis and severity of the disease. Materials and Methods: The oral mucosa was clinically examined in 100 randomly selected Syrian psoriatic patients presented to the Dermatological Diseases Hospital in Damascus University, Syria (February 2009 - December 2010), and in 100 matched controls. PASI index was used to evaluate the disease severity. Chi-square and Student t-test were used to compare differences between groups. Results: Oral mucosal lesions were observed in 72% of the psoriasis cases, while 46% of the control group’s subjects had oral lesions. Fissured tongue, geographic tongue, and red lesions were detected in 36%, 25%, and 7% of the examined psoriatics, respectively. These lesions were significantly more frequent in the psoriatics than in the controls. A correlation was found between furred tongue and the age of the psoriasis patients. However, an association was observed for fissured tongue, furred tongue with the severity of the disease, and for fissured tongue, white lesions, cheilitis with nail involvement. However, no correlation with the psoriasis types was recorded. Conclusion: Some oral mucosal lesions were associated with psoriasis, so these lesions may be considered as oral manifestations of this disease, and should be taken into account in new studies as possible predictors or markers of this dermatitis. Further studies are recommended to confirm these oral manifestations.

Keywords: psoriasis, tongue, mucosa, lesions

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Authors: Imran Khan Pathan, Anil Bhandari, Peeyush K. Sharma, Rakesh K. Patel, Suresh Purohit

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Floating tablets of Marichyadi Vati were developed with an aim to prolong its gastric residence time and increase the bioavailability of drug. Rapid gastrointestinal transit could result in incomplete drug release from the drug delivery system above the absorption zone leading to diminished efficacy of the administered dose. The tablets were prepared by wet granulation technique, using HPMC E50 LV act as Matrixing agent, Carbopol as floating enhancer, microcrystalline cellulose as binder, sodium bi carbonate as effervescent agent with other excipients. The simplex lattice design was used for selection of variables for tablets formulation. Formulation was optimized on the basis of floating time and in vitro drug release. The results showed that the floating lag time for optimized formulation was found to be 61 second with about 97.32 % of total drug release within 3 hours. The in vitro release profiles of drug from the formulation could be best expressed zero order with highest linearity r2 = 0.9943. It was concluded that the gastroretentive drug delivery system can be developed for Marichyadi Vati containing piperine to increase the residence time of the drug in the stomach and thereby increasing bioavailability.

Keywords: piperine, Marichyadi Vati, gastroretentive drug delivery, floating tablet

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Authors: Emma E. Hellawell, Susan J. Hughes

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BBrownfield sites are currently being redeveloped for residential use. Information on soil contamination on these former industrial sites is collected as part of the planning process by the local government. This research project analyses this untapped resource of environmental data, using site investigation data submitted to a local Borough Council, in Surrey, UK. Over 150 site investigation reports were collected and interrogated to extract relevant information. This study involved three phases. Phase 1 was the development of a database for soil contamination information from local government reports. This database contained information on the source, history, and quality of the data together with the chemical information on the soil that was sampled. Phase 2 involved obtaining site investigation reports for development within the study area and extracting the required information for the database. Phase 3 was the data analysis and interpretation of key contaminants to evaluate typical levels of contaminants, their distribution within the study area, and relating these results to current guideline levels of risk for future site users. Preliminary results for a pilot study using a sample of the dataset have been obtained. This pilot study showed there is some inconsistency in the quality of the reports and measured data, and careful interpretation of the data is required. Analysis of the information has found high levels of lead in shallow soil samples, with mean and median levels exceeding the current guidance for residential use. The data also showed elevated (but below guidance) levels of potentially carcinogenic polyaromatic hydrocarbons. Of particular concern from the data was the high detection rate for asbestos fibers. These were found at low concentrations in 25% of the soil samples tested (however, the sample set was small). Contamination levels of the remaining chemicals tested were all below the guidance level for residential site use. These preliminary pilot study results will be expanded, and results for the whole local government area will be presented at the conference. The pilot study has demonstrated the potential for this extensive dataset to provide greater information on local contamination levels. This can help inform regulators and developers and lead to more targeted site investigations, improving risk assessments, and brownfield development.

Keywords: Brownfield development, contaminated land, local government planning data, site investigation

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Authors: Shirin Sarejloo

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Background: Electrophysiological-related manifestation of COVID-19 is a matter of debate in the literature nowadays. A wide spectrum of arrhythmias was observed among patients who have been infected with COVID-19. Objectives: This study discussed the prevalence of arrhythmias and conduction system disease in patients with COVID-19. Method: In this retrospective study, demographic and electrocardiographic data of 432 expired COVID-19 patients who had been admitted to Faghihi Hospital of Shiraz University of Medical Sciences from August2020 until December 2020 were reviewed. Results: Atrioventricular nodal block (AVB) was found in 40(9.3%) patients. Furthermore, 28(6.5%) of them suffered from the first degree of AVB, and 12(2.8%) suffered from complete heart block (CHB). Among 189 cases (59.0%), ST-T changes agreed with myocardial infarction or localized myocarditis. Findings of myocardial injury, including fragmented QRS and prolonged QTc were observed among 91 (21.1%) and 28 (6.5%), respectively. In victims of COVID-19, conduction disease was not related to any comorbidities. Fragmented QRS, axis deviation, presence of S1Q3T3, and poor R wave progression were significantly related to conduction system abnormalities in victims of COVID-19 (P-value > 0.05). Conclusion: Our findings can serve in future studies that aim to develop a risk stratification method for susceptible COVID-19 patients. The myocardial injury appears to role significantly in COVID-19 morbidity and mortality. Consequently, we recommend health policymakers consider separate catheterization laboratories that provide service only to COVID-19 patients.

Keywords: COVID-19, conduction system, ECG, atrioventricular block

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Authors: Eliza Torrigue, Efrelyn Iellamo

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Maternal death is one of the rising health issues in the Philippines. It is alarming to know that in every hour of each day, a mother gives birth to a child who may not live to see the next day. Statistics shows that intrapartum period and third stage of labor are the very crucial periods for the expectant mother, as well as the first six hours of life for the newborn. To address the issue, The Essential Intrapartum Newborn Care (EINC) was developed. Through this, Obstetric Delivery Room (OB-DR) Nurses shall be updated with the evidence-based maternal and newborn care to ensure patient safety, thus, reducing maternal and child mortality. This study aims to describe the compliance of hospitals, especially of OB-DR nurses, to the EINC Protocols. The researcher aims to link the profile variables of the respondents in terms of age, length of service and formal training to their compliance on the EINC Protocols. The outcome of the study is geared towards the development of appropriate training program for OB-DR Nurses assigned in the delivery room of the hospitals based on the study’s results to sustain the EINC standards. A descriptive correlational method was used. The sample consists of 75 Obstetric Delivery Room (OB-DR) Nurses from three government hospitals in the City of Manila namely, Ospital ng Maynila Medical Center, Tondo Medical Center, and Gat Andres Bonifacio Memorial Medical Center. Data were collected using an evaluative checklist. Ranking, weighted mean, Chi-square and Pearson’s R were used to analyze data. The level of compliance to the EINC Protocols by the respondents was evaluated with an overall mean score of 4.768 implying that OB-DR Nurses have a high regard in complying with the step by step procedure of the EINC. Furthermore, data shows that formal training on EINC have a significant relationship with OB-DR Nurses’ level of compliance during cord care, AMTSL, and immediate newborn care until the first ninety minutes to six hours of life. However, the respondents’ age and length of service do not have a significant relationship with the compliance of OB-DR Nurses on EINC Protocols. In the pursuit of decreasing the maternal mortality in the Philippines, EINC Protocols have been widely implemented in the country especially in the government hospitals where most of the deliveries happen. In this study, it was found out that OB-DR Nurses adhere and are highly compliant to the standards in order to assure that optimum level of care is delivered to the mother and newborn. Formal training on EINC, on the other hand, create the most impact on the compliance of nurses. It is therefore recommended that there must be a structured enhancement training program to plan, implement and evaluate the EINC protocols in these government hospitals.

Keywords: compliance, intrapartum, newborn care, nurses

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Authors: Manirath Wongsim

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Information Quality (IQ) has become a critical, strategic issue in Accounting Information Systems (AIS) adoption. In order to implement AIS adoption successfully, it is important to consider the quality of information use throughout the adoption process, which seriously impacts the effectiveness of AIS adoption practice and the optimization of AIS adoption decisions. There is a growing need for research to provide insights into issues and solutions related to IQ in AIS adoption. The need for an integrated approach to improve IQ in AIS adoption, as well as the unique characteristics of accounting data, demands an AIS adoption specific IQ framework. This research aims to explore ways of managing information quality and AIS adoption to investigate the relationship between the IQ issues and AIS adoption process. This study has led to the development of a framework for understanding IQ management in AIS adoption. This research was done on 44 respondents as ten organisations from manufacturing firms in Thailand. The findings of the research’s empirical evidence suggest that IQ dimensions in AIS adoption to provide assistance in all process of decision making. This research provides empirical evidence that information quality of AIS adoption affect decision making and suggests that these variables should be considered in adopting AIS in order to improve the effectiveness of AIS.

Keywords: information quality, information quality dimensions, accounting information systems, accounting information system adoption

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Authors: Theresa Bacon-Baguley, Martina Reinhold

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Introduction: Evaluation and analysis are the cornerstones of any successful program in higher education. When developing a program at a distant campus, it is essential that the process of evaluation and analysis be orchestrated in a timely manner with tools that can identify both the positive and negative components of distant education. We describe the utilization of a newly developed tool used to evaluate and analyze the successful expansion to a distant campus using Telepresence Technology. Like interactive television, Telepresence allows live interactive delivery but utilizes broadband cable. The tool developed is adaptable to any distant campus as the framework for the tool was derived from a systematic review of the literature. Methodology: Because Telepresence is a relatively new delivery system, the evaluation tool was developed based on a systematic review of literature in the area of distant education and ITV. The literature review identified four potential areas of concern: 1) technology, 2) confidence in the system, 3) faculty delivery of the content and, 4) resources at each site. Each of the four areas included multiple sub-components. Benchmark values were determined to be 80% or greater positive responses to each of the four areas and the individual sub-components. The tool was administered each semester during the didactic phase of the curriculum. Results: Data obtained identified site-specific issues (i.e., technology access, student engagement, laboratory access, and resources), as well as issues common at both sites (i.e., projection screen size). More specifically, students at the parent location did not have adequate access to printers or laboratory space, and students at the distant campus did not have adequate access to library resources. The evaluation tool identified that both sites requested larger screens for visualization of the faculty. The deficiencies were addressed by replacing printers, including additional orientation for students on library resources and increasing the screen size of the Telepresence system. When analyzed over time, the issues identified in the tool as deficiencies were resolved. Conclusions: Utilizing the tool allowed adjustments of the Telepresence delivery system in a timely manner resulting in successful implementation of an entire curriculum at a distant campus.

Keywords: physician assistant, telepresence technology, distant education, assessment

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Authors: Atucungwiire Rwebiita

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Introduction: In Uganda, provision of adolescent sexual reproductive health and rights (SRHR) services for key population is still hindered by negative attitudes, stigma and discrimination (S&D) at both the community and facility levels. To address this barrier, Integrated Community Based Initiatives (ICOBI) with support from SIDA is currently implementing a quality improvement (QI) innovative approach for strengthening the capacity of key population (KP) peer leaders and health workers to deliver friendly SRHR services without S&D. Methods: Our innovative approach involves continuous mentorship and coaching of 8 QI teams at 8 health facilities and their catchment areas. Each of the 8 teams (comprised of 5 health workers and 5 KP peer leaders) are facilitated twice a month by two QI Mentors in a 2-hour mentorship session over a period of 4 months. The QI mentors were provided a 2-weeks training on QI approaches for reducing S&D against young key populations in the delivery of SRHR Services. The mentorship sessions are guided by a manual where teams base to analyse root causes of S&D and develop key performance indicators (KPIs) in the 1st and 2nd second sessions respectively. The teams then develop action plans in the 3rd session and review implementation progress on KPIs at the end of subsequent sessions. The KPIs capture information on the attitude of health workers and peer leaders and the general service delivery setting as well as clients’ experience. A dashboard is developed to routinely track the KPIs for S&D across all the supported health facilities and catchment areas. After 4 months, QI teams share documented QI best practices and tested change packages on S&D in a learning and exchange session involving all the teams. Findings: The implementation of this approach is showing positive results. So far, QI teams have already identified the root causes of S&D against key populations including: poor information among health workers, fear of a perceived risk of infection, perceived links between HIV and disreputable behaviour. Others are perceptions that HIV & STIs are divine punishment, sex work and homosexuality are against religion and cultural values. They have also noted the perception that MSM are mentally sick and a danger to everyone. Eight QI teams have developed action plans to address the root causes of S&D. Conclusion: This approach is promising, offers a novel and scalable means to implement stigma-reduction interventions in facility and community settings.

Keywords: key populations, sexual reproductive health and rights, stigma and discrimination , quality improvement approach

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Authors: Septiawan A. Saputro, Purnami Widyaningsih, Sutanto Sastraredja

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Measles is a disease which can spread caused by a virus and has been a priority’s Ministry of Health in Indonesia to be solved. Each infected person can be recovered and get immunity so that the spread of the disease can be constructed with susceptible infected recovered (SIR). To prevent the spread of measles transmission, the Ministry of Health holds vaccinations program. The aims of the research are to derive susceptible vaccinated infected recovered (SVIR) model, to determine the patterns of disease spread with SVIR model, and also to apply the SVIR model on the spread of measles in Indonesia. Based on the article, it can be concluded that the spread model of measles with vaccinations, that is SVIR model. It is a first-order differential equation system. The patterns of disease spread is determined by solution of the model. Based on that model Indonesia will be a measles-free nation in 2186 with the average of vaccinations scope about 88% and the average score of vaccinations failure about 4.9%. If it is simulated as Ministry of Health new programs with the average of vaccinations scope about 95% and the average score of vaccinations failure about 3%, then Indonesia will be a measles-free nation in 2184. Even with the average of vaccinations scope about 100% and no failure of vaccinations, Indonesia will be a measles-free nation in 2183. Indonesia’s target as a measles-free nation in 2020 has not been reached.

Keywords: measles, vaccination, susceptible infected recovered (SIR), susceptible vaccinated infected recovered (SVIR)

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Authors: Anita Paddy, Millicent Obodai, Lebbaeus Asamani

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The management of sickle cell disease requires a multidisciplinary team for better outcomes. Thus, literature on the application of the biopsychosocial model for the management and explanation of chronic pain in sickle cell disease (SCD) and other chronic diseases abound. However, there is limited research on the use of the biopsychosocial model, together with a spiritual component (biopsychosocial-spiritual model). The study investigated the extent to which healthcare providers utilized the biopsychosocial-spiritual model in the management of chronic pain to improve the quality of life (QoL) of patients with SCD. This study employed the descriptive survey design involving a consecutive sampling of 261 patients with SCD who were between the ages of 18 to 79 years and were accessing hematological services at the Clinical Genetics Department of the Korle Bu Teaching Hospital. These patients willingly consented to participate in the study by appending their signatures. The theory of integrated quality of life, the gate control theory of pain and the biopsychosocial(spiritual) model were tested. An instrument for the biopsychosocial-spiritual model was developed, with a basis from the literature reviewed, while the World Health Organisation Quality of Life BREF (WHOQoLBref) and the spirituality rating scale were adapted and used for data collection. Data were analyzed using descriptive statistics (means, standard deviations, frequencies, and percentages) and partial least square structural equation modeling. The study revealed that healthcare providers had a great leaning toward the biological domain of the model compared to the other domains. Hence, participants’ QoL was not fully improved as suggested by the biopsychosocial(spiritual) model. Again, the QoL and spirituality of patients with SCD were quite high. A significant negative impact of spirituality on QoL was also found. Finally, the biosocial domain of the biopsychosocial-spiritual model was the most significant predictor of QoL. It was recommended that policymakers train healthcare providers to integrate the psychosocial-spiritual component in health services. Also, education on SCD and its resultant impact from the domains of the model should be intensified while health practitioners consider utilizing these components fully in the management of the condition.

Keywords: biopsychosocial (spritual), sickle cell disease, quality of life, healthcare, accra

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Authors: İbrahi̇m Kara, Seher Arslankaya

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Frequently preferred in the field of engineering in particular, data mining has now begun to be used in the field of health as well since the data in the health sector have reached great dimensions. With data mining, it is aimed to reveal models from the great amounts of raw data in agreement with the purpose and to search for the rules and relationships which will enable one to make predictions about the future from the large amount of data set. It helps the decision-maker to find the relationships among the data which form at the stage of decision-making. In this study, it is aimed to determine the risk of heart attack at the first stage, to control it, and to make its resource planning with the method of data mining. Through the early and correct diagnosis of heart attacks, it is aimed to reveal the factors which affect the diseases, to protect health and choose the right treatment methods, to reduce the costs in health expenditures, and to shorten the durations of patients’ stay at hospitals. In this way, the diagnosis and treatment costs of a heart attack will be scrutinized, which will be useful to determine the risk of the disease at the first stage, to control it, and to make its resource planning.

Keywords: data mining, decision support systems, heart attack, health sector

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Authors: Uwizera Egide

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Introduction: Dermatological conditions are one of the most burdensome diseases in our health system. Global studies suggest that around 1 in 3 people gets a skin disease at a certain point in their life, though this does not necessarily guarantee the urge to consult. For a high-ranking disease, it is surprising how there is not enough data to support its effect on the economy and the general health system impact. It is for that reason that this study’s aim is to identify the burden of dermatological conditions in Rwanda so as to have a general picture of what our population is going through in regards to dermatological conditions. Methods: We used a cross sectional retrospective study. Data were obtained from patient’s information recorded in an open clinic at CHUB in a period of six months from July to December of the year 2021. Results: The study had a total of 4600 patients who attended dermatology service in a period of six months from July to December of the year 2021. We found a list of 102 dermatological diseases that presented at variable rates. The most prevalent disease was atopic dermatitis, at a rate of 23%. About 90% of presented conditions had only one choice of treatment from the hospital pharmacy. Most patients who presented were between 18-35 years old and with a predominance of the female gender; the level of education was either secondary or University Degree in our study, 65.4% of patients who presented were female; the majority, around 45% were between 18-35 years old, mostly being single 56%. The majority came from Southern province as it is the location of the hospital. The insurance mostly used was community-based health insurance with 63.8%, followed by RSSB with 18.5%, MS/UR, and other private insurances. The frequency of group drugs prescribed among all dermatological medications, steroids were the most commonly given medications at a rate of 39%, followed by emollients, antibiotics, and antifungal. The drugs prescribed were mostly available in the pharmacy of CHUB, with 60% and 40% being found in pharmacies outside the hospital. Conclusion: Dermatological conditions are prevalent in all age groups and distributed through all socioeconomic classes. About 9.2% of patient who consulted CHUB in 2021 presented one Dermatological condition of which 40 % of prescribed medications is never found in Hospital urging a need to buy medication in private pharmacies with more expenses and a risk of not complying on prescribed medication if in case they can’t afford paying them outside the CHUB. This finding urges a need to avail all essential dermatological drugs in hospital pharmacies to allow our patients to get them for the proper compliance of prescribed drugs in the management of skin diseases.

Keywords: atopic dermatitis, CHUB (centre hopitalier univerisitaire de butare), dermatological condition, fungal infections

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Authors: Yichao Liu, Peter Fransson, Julian Heidecke, Jonas Wallin, Joacim Rockloev

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Dengue, a mosquito-borne viral disease, poses a significant public health challenge in endemic tropical or subtropical countries, including Sri Lanka. To reveal insights into the complexity of the dynamics of this disease and study the drivers, a comprehensive model capable of both robust forecasting and insightful inference of drivers while capturing the co-circulating of several virus strains is essential. However, existing studies mostly focus on only one aspect at a time and do not integrate and carry insights across the siloed approach. While mechanistic models are developed to capture immunity dynamics, they are often oversimplified and lack integration of all the diverse drivers of disease transmission. On the other hand, purely data-driven methods lack constraints imposed by immuno-epidemiological processes, making them prone to overfitting and inference bias. This research presents a hybrid model that combines machine learning techniques with mechanistic modelling to overcome the limitations of existing approaches. Leveraging eight years of newly reported dengue case data, along with socioeconomic factors, such as human mobility, weekly climate data from 2011 to 2018, genetic data detecting the introduction and presence of new strains, and estimates of seropositivity for different districts in Sri Lanka, we derive a data-driven vector (SEI) to human (SEIR) model across 16 regions in Sri Lanka at the weekly time scale. By conducting ablation studies, the lag effects allowing delays up to 12 weeks of time-varying climate factors were determined. The model demonstrates superior predictive performance over a pure machine learning approach when considering lead times of 5 and 10 weeks on data withheld from model fitting. It further reveals several interesting interpretable findings of drivers while adjusting for the dynamics and influences of immunity and introduction of a new strain. The study uncovers strong influences of socioeconomic variables: population density, mobility, household income and rural vs. urban population. The study reveals substantial sensitivity to the diurnal temperature range and precipitation, while mean temperature and humidity appear less important in the study location. Additionally, the model indicated sensitivity to vegetation index, both max and average. Predictions on testing data reveal high model accuracy. Overall, this study advances the knowledge of dengue transmission in Sri Lanka and demonstrates the importance of incorporating hybrid modelling techniques to use biologically informed model structures with flexible data-driven estimates of model parameters. The findings show the potential to both inference of drivers in situations of complex disease dynamics and robust forecasting models.

Keywords: compartmental model, climate, dengue, machine learning, social-economic

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Authors: Vithaya Intaraphimol

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This research investigates the effect of financial accounting information and non-financial accounting reports on corporate credibility via strength of board of directors and market environment volatility as moderating effect. Data in this research is collected by questionnaire form non-financial companies listed on the Stock Exchange of Thailand. Multiple regression statistic technique is chosen for analyzing the data. The empirical results find that firms with greater financial accounting information reports and non-financial accounting information reports will gain greater corporate credibility. Therefore, the corporate reporting has the value for the firms. Moreover, the strength of board of directors will positively moderate the financial and non-financial accounting information reports and corporate credibility relationship. Whereas, market environment volatility will negatively moderate the financial and nonfinancial accounting information reports and corporate credibility relationship.

Keywords: corporate credibility, financial and non-financial reports, firms performance, economics

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Authors: Noorulain Khalid, Unsaar Hayat, Muhammad Chaudhary, Christos Iosifidis, Felipe Dhawahir-Scala, Fiona Carley

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Dry eye disease (DED) is a common condition seen in the emergency eye department (EED) at Manchester Royal Eye Hospital (MREH). However, there is variability in the prescription of lubricating eye drops among different healthcare providers. The aim of this study was to develop an up-to-date, standardized algorithm for the prescription of lubricating eye drops in the EED at MREH based on international and national guidelines. The study also aimed to assess the impact of implementing the guideline on the rate of inappropriate lubricant prescriptions. Primarily, the impact was to be assessed in the form of the appropriateness of prescriptions for patients’ DED. The impact was secondary to be assessed through analysis of the cost to the hospital. Data from 845 patients who attended the EED over a 3-month period were analyzed, and 157 patients met the inclusion and exclusion criteria. After conducting a review of the literature and collaborating with the corneal team, an algorithm for the prescription of lubricants in the EED was developed. Three plan-do-study-act (PDSA) cycles were conducted, with interventions such as emails, posters, in-person reminders, and education for incoming trainees. The appropriateness of prescriptions was evaluated against the guidelines. Data were collected from patient records and analyzed using statistical methods. The appropriateness of prescriptions was assessed by comparing them to the guidelines and by clinical correlation with a specialized registrar. The study found a substantial improvement in the number of appropriate prescriptions, with an increase from 55% to 93% over the three PDSA cycles. There was additionally a 51% reduction in expenditure on lubricant prescriptions, resulting in cost savings for the hospital (approximate saving of £50/week). Theoretical importance: Appropriate prescription of lubricating eye drops improves disease management for patients and reduces costs for the hospital. The development and implementation of a standardized guideline facilitate the achievement of these goals. Conclusion: This study highlights the inconsistent management of DED in the EED and the potential lack of training in this area for healthcare providers. The implementation of a standardized, easy-to-follow guideline for lubricating eye drops can help to improve disease management while also resulting in cost savings for the hospital.

Keywords: lubrication, dry eye disease, guideline, prescription

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Authors: Aisha Giwa, Mohammed-Faosy Adeniran, Olufunke Femi-Ojo

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Four decades ago, the World Health Organization (WHO) launched the Expanded Programme on Immunization (EPI). The EPI blueprint laid out the technical and managerial functions necessary to routinely vaccinate children with a limited number of vaccines, providing protection against diphtheria, tetanus, whooping cough, measles, polio, and tuberculosis, and to prevent maternal and neonatal tetanus by vaccinating women of childbearing age with tetanus toxoid. Despite global efforts, the Routine Immunization (RI) coverage in two of the World Health Organization (WHO) regions; the African Region and the South-East Asia Region, still remains short of its targets. As a result, the WHO Regional Director for Africa declared 2012 as the year for intensifying RI in these regions and this also coincided with the declaration of polio as a programmatic emergency by the WHO Executive Board. In order to intensify routine immunization, the National Routine Immunization Strategic Plan (2013-2015) stated that its core priority is to ensure 100% adequacy and availability of vaccines for safe immunization. To achieve 100% availability, the “PUSH System” and then “Push-Plus” were adopted for vaccine distribution, which replaced the inefficient “PULL” method. The NPHCDA plays the key role in coordinating activities in area advocacy, capacity building, engagement of 3PL for the state as well as monitoring and evaluation of the vaccine delivery process. eHealth Africa (eHA) is a player as a 3PL service provider engaged by State Primary Health Care Boards (SPHCDB) to ensure vaccine availability through Vaccine Direct Delivery (VDD) project which is essential to successful routine immunization services. The VDD project ensures the availability and adequate supply of high-quality vaccines and immunization-related materials to last-mile facilities. eHA’s commitment to the VDD project saw the need for an assessment of the project vis-a-vis the overall project performance, evaluation of a process for necessary improvement suggestions as well as general impact across Kano State (Where eHA had transitioned to the state), Bauchi State (currently manage delivery to all LGAs except 3 LGAs currently being managed by the state), Sokoto State (eHA currently covers all LGAs) and Zamfara State (Currently, in-sourced and managed solely by the state).

Keywords: cold chain logistics, health supply chain system strengthening, logistics management information system, vaccine delivery traceability and accountability

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Authors: Mostafa Gamal, Hoda K. Mohamed, Islam El-Maddah, Ali Hamdi

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In recent years, many digital documents on the web have been created due to the rapid growth of ’social applications’ communities or ’Data-intensive applications’. The evolution of online-based multimedia data poses new challenges in storing and querying large amounts of data for online recommender systems. Graph data models have been shown to be more efficient than relational data models for processing complex data. This paper will explain the key differences between graph and relational databases, their strengths and weaknesses, and why using graph databases is the best technology for building a realtime recommendation system. Also, The paper will discuss several similarity metrics algorithms that can be used to compute a similarity score of pairs of nodes based on their neighbourhoods or their properties. Finally, the paper will discover how NLP strategies offer the premise to improve the accuracy and coverage of realtime recommendations by extracting the information from the stored unstructured knowledge, which makes up the bulk of the world’s data to enrich the graph database with this information. As the size and number of data items are increasing rapidly, the proposed system should meet current and future needs.

Keywords: graph databases, NLP, recommendation systems, similarity metrics

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