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نتیجه جستجو - Public health

تعداد مقالات یافته شده: 119
ردیف عنوان نوع
1 Adverse Reaction Detection from Social Media based on Quantum Bi-LSTM with Attention
تشخیص واکنش نامطلوب از رسانه های اجتماعی بر اساس کوانتوم Bi-LSTM با توجه-2022
Drug combination is very common in the course of disease treatment. However, it inevitably increases the overall risk of adverse drug reactions (ADRs). It is very important to early and accurately detect and identify the potential ADRs for combined medication safety and public health. Social media is an important pharmacovigilance data source for ADR detection. But the data are complex, mass, clutter, highly sparse, so it is difficult to detect the ADR information from these data. Deep learning stands out in terms of increased accuracy. However, it takes a lot of training time and requires a lot of computing power. Quantum computing has strong parallel computing capability, and requires less computing power. By introducing attention mechanism and quantum computing into Bi-directional Long Short-Term Memory (Bi-LSTM), a quantum Bi-LSTM with attention (QBi-LSTMA) model is constructed for ADR detection from social media big data. QBi-LSTMA is composed of 6 variable component subcircuits (VQC) stacked. Under the condition that the main topology of Bi-LSTM remains unchanged, the biases of QBi-LSTMA in input gate, forgetting gate, candidate memory unit and output gate are removed to simplify the network structure, and the weight and active value qubits of the model are used to update the network weight. The performance of the proposed method is evaluated on the SMM4H dataset, comparing with one traditional ADR detection method and three deep learning based ADR detection approaches. The experiment results show that the proposed method has great potential in ADRs detection. To the best of our knowledge, this is the first time to investigate quantum computing to detect ADRs from social media big data.
INDEX TERMS: Social media big data | Adverse drug reactions (ADRs) | Bi-directional Long Short-Term Memory (Bi-LSTM) | Quantum Bi-LSTM with attention (QBi-LSTMA).
مقاله انگلیسی
2 Algebraic Attacks on Block Ciphers Using Quantum Annealing
حملات جبری به رمزهای بلوکی با استفاده از آنیل کوانتومی-2022
Drug combination is very common in the course of disease treatment. However, it inevitably increases the overall risk of adverse drug reactions (ADRs). It is very important to early and accurately detect and identify the potential ADRs for combined medication safety and public health. Social media is an important pharmacovigilance data source for ADR detection. But the data are complex, mass, clutter, highly sparse, so it is difficult to detect the ADR information from these data. Deep learning stands out in terms of increased accuracy. However, it takes a lot of training time and requires a lot of computing power. Quantum computing has strong parallel computing capability, and requires less computing power. By introducing attention mechanism and quantum computing into Bi-directional Long Short-Term Memory (Bi-LSTM), a quantum Bi-LSTM with attention (QBi-LSTMA) model is constructed for ADR detection from social media big data. QBi-LSTMA is composed of 6 variable component subcircuits (VQC) stacked. Under the condition that the main topology of Bi-LSTM remains unchanged, the biases of QBi-LSTMA in input gate, forgetting gate, candidate memory unit and output gate are removed to simplify the network structure, and the weight and active value qubits of the model are used to update the network weight. The performance of the proposed method is evaluated on the SMM4H dataset, comparing with one traditional ADR detection method and three deep learning based ADR detection approaches. The experiment results show that the proposed method has great potential in ADRs detection. To the best of our knowledge, this is the first time to investigate quantum computing to detect ADRs from social media big data.
INDEX TERMS: Social media big data | Adverse drug reactions (ADRs) | Bi-directional Long Short-Term Memory (Bi-LSTM) | Quantum Bi-LSTM with attention (QBi-LSTMA).
مقاله انگلیسی
3 Evaluation of six commercial SARS-CoV-2 rapid antigen tests in nasopharyngeal swabs: Better knowledge for better patient management?
ارزیابی شش تست آنتی ژن سریع SARS-COV-2 در سواب های نازوفارنکس: دانش بهتر برای مدیریت بهتر بیمار؟-2021
Robust antigen point-of-care SARS-CoV-2 tests have been proposed as an efficient tool to address the COVID-19 pandemic. This requirement was raised after acknowledging the constraints that are brought by molecular biology. However, worldwide markets have been flooded with cheap and potentially underperforming lateral flow assays. Herein we retrospectively compared the overall performance of five qualitative rapid antigen SARS- CoV-2 assays and one quantitative automated test on 239 clinical swabs. While the overall sensitivity and specificity are relatively similar for all tests, concordance with molecular based methods varies, ranging from 75,7% to 83,3% among evaluated tests. Sensitivity is greatly improved when considering patients with higher viral excretion (Ct≤33), proving that antigen tests accurately distinguish infectious patients from viral shedding. These results should be taken into consideration by clinicians involved in patient triage and management, as well as by national authorities in public health strategies and for mass campaign approaches.
keywords: SARS-DONE-2 | تست های آنتی ژن سریع | rt-pcr | کووید -19 | SARS-CoV-2 | Rapid antigen tests | RT-PCR | COVID-19
مقاله انگلیسی
4 Digital Livestock Farming
دامداری دیجیتال-2021
As the global human population increases, livestock agriculture must adapt to provide more livestock products and with improved efficiency while also addressing concerns about animal welfare, environmental sustainability, and public health. The purpose of this paper is to critically review the current state of the art in digitalizing animal agriculture with Precision Livestock Farming (PLF) technologies, specifically biometric sensors, big data, and blockchain technology. Biometric sensors include either noninvasive or invasive sensors that monitor an individual animal’s health and behavior in real time, allowing farmers to integrate this data for population-level analyses. Real-time information from biometric sensors is processed and integrated using big data analytics systems that rely on statistical algorithms to sort through large, complex data sets to provide farmers with relevant trending patterns and decision-making tools. Sensors enabled blockchain technology affords secure and guaranteed traceability of animal products from farm to table, a key advantage in monitoring disease outbreaks and preventing related economic losses and food-related health pandemics. Thanks to PLF technologies, livestock agriculture has the potential to address the abovementioned pressing concerns by becoming more transparent and fostering increased consumer trust. However, new PLF technologies are still evolving and core component technologies (such as blockchain) are still in their infancy and insufficiently validated at scale. The next generation of PLF technologies calls for preventive and predictive analytics platforms that can sort through massive amounts of data while accounting for specific variables accurately and accessibly. Issues with data privacy, security, and integration need to be addressed before the deployment of multi-farm shared PLF solutions be- comes commercially feasible. Implications Advanced digitalization technologies can help modern farms optimize economic contribution per animal, reduce the drudgery of repetitive farming tasks, and overcome less effective isolated solutions. There is now a strong cultural emphasis on reducing animal experiments and physical contact with animals in-order-to enhance animal welfare and avoid disease outbreaks. This trend has the potential to fuel more research on the use of novel biometric sensors, big data, and blockchain technology for the mutual benefit of livestock producers, consumers, and the farm animals themselves. Farmers’ autonomy and data-driven farming approaches compared to experience-driven animal manage- ment practices are just several of the multiple barriers that digitalization must overcome before it can become widely implemented.
Keywords: Precision Livestock Farming | digitalization | Digital Technologies in Livestock Systems | sensor technology | big data | blockchain | data models | livestock agriculture
مقاله انگلیسی
5 Self-management on heart failure: A meta-analysis
خود مدیریتی در نارسایی قلبی: متاآنالیز-2021
Background and aims: Heart failure (HF) is a severe public health problem all over the World. Selfmanagement is an effective method to progress self-care ability. However, the role of selfmanagement in heart failure has not been thoroughly elucidated.
Methods: The research articles related to heart failure were searched by the PubMed, Embase, Cochrane databases, and China National Knowledge Database on articles published through March 2020. The average 95% of confidence intervals (CIs) were used to calculate using random-effects or fixed-effects. Review Manager (version 5.2) was adopted for meta-analysis, sensitivity analysis, and bias analysis.
Results: Eight (8) eligible studies with 1707 patients with HF were included in this analysis. In the Metaanalysis showed significant differences for Self-management (SM) groups in Dutch Heart Failure Knowledge Scale (DHFK) (MD ¼ 1.36, 95%CI [-0.03, 2.75], P ¼ 0.04; I2 ¼ 83%), in Self-Care of Heart Failure Index (SCHFI) (MD ¼ 5.51, 95%CI [0.62, 10.40], P ¼ 0.03; I2 ¼ 70%), and in Self-Efficacy for Managing Chronic Disease Scale (SEMCDI) (I2 ¼ 47%, Z ¼ 5.43, P of over effect < 0.0001) than control groups. One bias is detected as attrition bias, and another one is reporting bias. Sensitivity analysis satisfied the stability of the results.
Conclusion: Self-management was associated with significant outcomes in patients with HF through knowledge, attitude, and practice (KAP).
keywords: نارسایی قلبی | خود مدیریت | می شود | متاآنالیز | Heart failure | Self-management | KAP | Meta-analysis
مقاله انگلیسی
6 Introducing an aflatoxin-safe labeling program in complex food supply chains: Evidence from a choice experiment in Nigeria
معرفی یک برنامه برچسب زدن بدون آفلاتوکسین در زنجیره های تأمین مواد غذایی پیچیده: شواهدی از یک آزمایش انتخاب در نیجریه-2021
Food contaminated with aflatoxins is one of the more prominent food safety issues facing developing countries. These toxins impose an immense burden on countries that have to deal with the repercussions of the contamination. Repercussions include increased public health concerns, increased health care expenditures, and other economic tolls. To alleviate these food safety concerns, the implementation of aflatoxin-safe certification can potentially incentivize and elevate food safety standards. This study uses a discrete choice experiment approach to assess if traders are willing to pay a price premium for aflatoxin-safe maize and whether such a premium varies across their market channels. Results indicate that maize traders who sell to other traders, large feed mills, food companies, and retailers exhibit a higher willingness to pay (WTP) for aflatoxin-safe certification compared to those who sell to small feed mills and consumers. Relevant policy implications are discussed.
Keywords: Aflatoxin contamination | Aflatoxin safe certification | Traders preferences | Traders willingness to pay | Maize, Nigeria
مقاله انگلیسی
7 Technology-enabled knowledge management for community healthcare workers: The effects of knowledge sharing and knowledge hiding
مدیریت دانش دانش تکنولوژی برای کارکنان بهداشت و درمان جامعه: اثرات به اشتراک گذاری دانش و پنهان کردن دانش-2021
The objective of this study is to explore different facet (dark and bright sides) of technology-enabled knowledge management (KM) for rural lay healthcare workers who belong to the bottom of pyramid (BoP) population in India. Data were collected through multiple rounds of engagements and semi-structured interviews with 37 Accredited Social Health Activists (ASHAs). Findings indicate the existence of spirals of value that are shaped by KM practices in such settings. Technology-enabled KM through knowledge-sharing is supporting an upward spiral of value creation at three different levels, i.e., the micro-level in the form of empowerment of ASHAs, the meso-level in the form of better healthcare for the rural Indian population, and the macro-level in the form of an effective public health policy outcome as envisioned by the government. Contrary to the technology-enabled KM through knowledge-sharing, technology-enabled KM through knowledge-hiding is eroding value resulting in failed attempts to use technology and reduced self-efficacy of ASHAs at the micro level. Technology-enabled KM through knowledge-hiding at the macro level is promoting stratification and marginalization within rural communities in India. Study leaves key implications for healthcare researchers, policymakers and businesses.
keywords: بهداشت روستایی | فعالان بهداشت اجتماعی | اقتصادهای نوظهور | تحقیق کیفی | پنهان کردن دانش | به اشتراک گذاری دانش | هندوستان | Rural healthcare | Social health activists | Emerging economies | Qualitative research | Knowledge-hiding | Knowledge-sharing | India
مقاله انگلیسی
8 Assessing the impact of drug courts on provider-directed marketing efforts by manufactures of medications for the treatment of opioid use disorder
ارزیابی تأثیر دادگاه های مواد مخدر در تلاشهای بازاریابی ارائه شده توسط تولیدکنندگان دارو برای درمان اختلال استفاده از مواد مخدر-2020
Background: Opioid use disorder (OUD) has become an increasingly consequential public health concern, especially in the United States where 47,600 opioid overdose deaths occurred in 2017 (Scholl, Seth, Kariisa, Wilson, & Baldwin, 2019). Medications for OUD (MOUD) are effective for decreasing opioid-related morbidity and mortality, including within the criminal justice system (Hedrich et al., 2012; Medications for Opioid Use Disorder Save Lives, 2019; Moore et al., 2019).While a stronger evidence base exists for agonist MOUD than for antagonist MOUD, a national study of drug courts found that half prohibited agonist MOUD (Matusow et al., 2013).Furthermore, recent media reports suggest that the pharmaceutical manufacturer of an antagonist MOUD has marketed its product towards drug court judges (Goodnough & Zernike, 2017; Harper, 2017). However, no study to date has systematically examined the relationship between MOUD marketing practices and drug courts. This ecological study examines the association at the county level between MOUD manufacturer payments to prescribers and drug court locations. Method: We extracted provider-directed payments from Centers for Medicare and Medicaid Services (CMS)s Sunshine Act Open Payments data 2014–2017, isolating those records mentioning any MOUD. We compared provider-directed payments for two major MOUDs: buprenorphine and extended-release naltrexone, in counties with and without drug courts. Results: The presence of any adult drug courts in the county is associated with a 7.86 percentage-point increase in the likelihood of providers in that county receiving any MOUD-related payments (about 22.46% of the sample mean, p<0.001) and with a 10.70% increase in the amount of these payments per 1000 county residents (p<0.001). The association between other forms of drug courts such as juvenile drug courts and Driving-Under-the-Influence courts (DUI) courts are less significant and slightly smaller in magnitude compared to those of adult drug courts. We did not find significant difference between payments by the manufacturer of Vivitrol and manufacturers of Zubsolv, Bunavail, and Suboxone (oral forms of buprenorphine). Conclusions: Our results show an ecological association at the county level between MOUD manufacturer payments to prescribers and drug court presence. However, we did not examine a causal association between these variables.
مقاله انگلیسی
9 New kid on the block: An investigation of the physical, operational, personnel, and service characteristics of recovery community centers in the United States
بچه های جدید در اپارتمان : بررسی خصوصیات جسمی ، عملیاتی ، پرسنلی و خدماتی مراکز جامعه بهبودی در ایالات متحده-2020
Background: Professional treatment and non-professional mutual-help organizations (MHOs) play important roles in mitigating addiction relapse risk. More recently, a third tier of recovery support services has emerged that are neither treatment nor MHO that encompass an all-inclusive flexible approach combining professionals and volunteers. The most prominent of these is Recovery Community Centers (RCCs). RCCs goal is to provide an attractive central recovery hub facilitating the accrual of recovery capital by providing a variety of services (e.g., recovery coaching; medication assisted treatment [MAT] support, employment/educational linkages). Despite their growth, little is known formally about their structure and function. Greater knowledge would inform the field about their potential clinical and public health utility. Method: On-site visits (2015–2016) to RCCs across the northeastern U.S. (K = 32) with semi-structured interviews conducted with RCC directors and online surveys with staff assessing RCCs: physicality and locality; operations and budgets; leadership and staffing; membership; and services. Results: Physicality and locality: RCCs were mostly in urban/suburban locations (90%) with very good to excellent Walk Scores reflecting easy accessibility. Ratings of environmental quality indicated neighborhood/ grounds/buildings were moderate-good attractiveness and quality. Operations: RCCs had been operating for an average of 8.5 years (SD = 6.2; range 1–33 years) with budgets (mostly state-funded) ranging from $17,000–$760,000/year, serving anywhere from a dozen to more than two thousand visitors/month. Leadership and staffing: Center directors were mostly female (55%) with primary drug histories of alcohol (62%), cocaine (19%), or opioids (19%). Most, but not all, directors (90%) and staff (84%) were in recovery. Membership: A large proportion of RCC visitors were male (61%), White (72%), unemployed (50%), criminal-justice system-involved (43%) and reported opioids (35%) or alcohol (33%) as their primary substance. Roughly half were in their first year of recovery (49%), but about 20% had five or more years. Services: RCCs reported a range of services including social/recreational (100%), mutual-help (91%), recovery coaching (77%), and employment (83%) and education (63%) assistance. Medication-assisted treatment (MAT) support (43%) and overdose reversal training (57%) were less frequently offered, despite being rated as highly important by staff. Conclusions: RCCs are easily accessible, attractive, mostly state-funded, recovery support hubs providing an array of services to individuals in various recovery stages. They appear to play a valued role in facilitating the accrual of social, employment, housing, and other recovery capital. Research is needed to understand the relative lack of opioid-specific support and to determine their broader impact in initiating and sustaining remission and cost-effectiveness.
Keywords: Recovery community centers | Recovery | Addiction | Support services | Recovery coaching | Addiction | Substance use disorder
مقاله انگلیسی
10 Nursing in the American Justice System
پرستاری در سیستم عدالت آمریکا-2020
Efforts to provide humane care for the mentally ill has led to growth of more suitable services in community-based settings, yet resources are insufficient to meet the needs of mentally ill who interface with the criminal justice system. The resulting collateral damage has created a pathway to prison for massive numbers of impaired individuals, and the inhumane warehousing of thousands of mentally ill people is reminiscent of a century ago. The criminal justice system was never intended to be a safety net for the public mental health system. While advances in expanding the role of the nurse in the healthcare system have shifted because of efforts by nursing’s response to the 2010 Institute of Medicine report, the challenges for correctional/ custody nursing have not been adequately articulated. This paper seeks to enhance awareness of Correctional Nursing through a discussion of challenges posed to nurses who work at the intersection of justice and public health in prisons, jails, detention centers and community supervision in this response to the Future of Nursing report.
مقاله انگلیسی
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