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نتیجه جستجو - پیوند داده

تعداد مقالات یافته شده: 4
ردیف عنوان نوع
1 Non-fatal drug overdose after release from prison: A prospective data linkage study
مصرف بیش از حد مواد مخدر غیر کشنده پس از آزادی از زندان: یک مطالعه پیوند داده ای آینده نگر-2020
Background: Adults released from prison are at increased risk of poor health outcomes and preventable mortality, including from overdose. Non-fatal overdose (NFOD) is a strong predictor of future overdose and associated with considerable morbidity. This study aims to the determine the incidence, predictors and clinical characteristics of NFOD following release from prison. Methods: We used pre-release interview data collected for a randomised controlled trial in 2008–2010, and linked person-level, state-wide ambulance, emergency department, and hospital records, from a representative sample of 1307 adults incarcerated in Queensland, Australia. The incidence of NFOD following release from prison was calculated. A multivariate Andersen-Gill model was used to identify demographic, health, social, and criminal justice predictors of NFOD. Results: The crude incidence rate (IR) of NFOD was 47.6 (95%CI 41.1–55.0) per 1000 person-years and was highest in the first 14 days after release from prison (IR=296 per 1000 person-years, 95%CI 206–426). In multivariate analyses, NFOD after release from prison was positively associated with a recent history of substance use disorder (SUD), dual diagnosis of mental illness and SUD, lifetime history of injecting drug use, lifetime history of NFOD, being dispensed benzodiazepines after release, a shorter index incarceration, and low perceived social support. The risk of NFOD was lower for people with high-risk alcohol use and while incarcerated. Conclusions: Adults released from prison are at high risk of non-fatal overdose, particularly in the first 14 days after release. Providing coordinated transitional care between prison and the community is likely critical to reduce the risk of overdose.
Keywords: Drug overdose | Prisons | Cohort studies | Ambulance | Hospital | Emergency medical services
مقاله انگلیسی
2 Opioid overdose death following criminal justice involvement: Linking statewide corrections and hospital databases to detect individuals at highest risk
مرگ با یش از حد مصرف مواد مخدر به دنبال درگیری عدالت کیفری: پیوند دادن به اصلاحات سراسر کشور و پایگاه داده های بیمارستان برای شناسایی افراد در معرض خطر-2020
Background: Persons who interact with criminal justice and hospital systems are particularly vulnerable to negative health outcomes, including overdose. However, the relationship between justice involvement, healthcare utilization and overdose risk is not well-understood. This data linkage study seeks to improve our understanding of the link between different types of justice involvement as well as hospital interaction and risk of fatal opioid overdose among persons with incarcerations, arrests and parole/probation records for drug and property crimes in Maryland. Methods: Maryland statewide criminal justice records were obtained for 2013–2016. Data were linked at the person-level to an all-payer hospitalization database and overdose death records for the same years. Logistic regression was performed to determine which criminal justice and hospital characteristics were associated with greatest risk of overdose death. Results: 89,591 adults had criminal-justice records and were included in the study. During the 2013–2016 study period, 4108 (4.59 %) were hospitalized for a non-fatal opioid overdose, and 519 (0.58 %) died of opioid overdose. Strongest risk factors for death included being older, being white, having had an inpatient or emergency hospitalization, having had more arrests, having been arrested for a drug charge (vs. property charge), having a misdemeanor drug charge (vs. a felony charge), and having been released from incarceration during the study period. Conclusion: Linking corrections and healthcare information can help advance understanding of risk and target overdose prevention interventions directed at justice-involved individuals with greatest need.
Keywords: Opioid overdose | Criminal justice | Hospitalization | Data linkage
مقاله انگلیسی
3 Linked open data-based explanations for transparent recommender systems
توضیحات مبتنی بر داده های باز پیوندی برای سیستم های پیشنهادی شفاف-2019
In this article we propose a framework that generates natural language explanations supporting the suggestions generated by a recommendation algorithm. The cornerstone of our approach is the usage of Linked Open Data (LOD) for explanation aims. Indeed, the descriptive properties freely available in the LOD cloud (e.g., the author of a book or the director of a movie) can be used to build a graph that connects the recommendations the user received to the items she previously liked via the properties extracted from the LOD cloud. In a nutshell, our approach is based on the insight that properties describing the items the user previously liked as well as the suggestions she received can be effectively used to explain the recommendations. Such a framework is both algorithm-independent and domain-independent , thus it can generate a natural lan- guage explanation for every kind of recommendation algorithm, and it can be used to explain a single recom- mendation ( Top-1 scenario) as well as a group of recommendations ( Top-N scenario). It is worth noting that the algorithm-independent characteristic does not mean that the framework is able to explain to the user how the recommendations have been generated and how the recommendation algorithm works. The framework explains to users why they might like the recommended items, independently from the recommendation algorithm that generated the recommendations. In the experimental evaluation, we carried out a user study (N = 680) aiming to investigate the effectiveness of our framework in three different domains, as movies, books and music . Results showed that our technique leads to transparent explanations for all the domains, and such explanations resulted independent of the specific recommendation algorithm in most of the experimental settings. Moreover, we also showed the goodness of our strategy when an entire group of recommendations has to be explained. As a case study, we integrated the framework in a real-world application, a conversational recommender system implemented as a Telegram Bot. The idea is to use the explanation for supporting both the training phase (when the user expresses her preferences) and the recommendation step (when the user receives the recommendations). Interesting outcomes emerge from these preliminary experiments.
Keywords: Linked open data | Explanation | Recommender systems | User interface | User study
مقاله انگلیسی
4 " ورودی کاهنده" پیچیده است؟ کنترل پلیس ، اقدامات امنیتی شخصی و جرم
سال انتشار: 2015 - تعداد صفحات فایل pdf انگلیسی: 10 - تعداد صفحات فایل doc فارسی: 15
در اینجا می خواهیم این ایده را که افزایش کنترل پلیس ( اقدامات امنیتی ) دولتی ، باعث چشم پوشی افراد از اقدامات امنیتی شخص می شود ( خطر اخلاقی ) با مفهوم " ورودیهای کاهنده" مبحث توابع تولید پیوند داده و پیشگیری از جرم را به عنوان خروجی دو " ورودی " یعنی کنترل پلیس ( کادوی همگانی ) و هزینه های امنیت شخصی مدل بندی کنیم . هم چنین نشان خواهیم داد افرادی که در پی مینیمم سازی هزینه اند برای بازداری کامل جرایم، هزینه های شخصی ناکافی در نظر بگیرند. افزایش کنترل پلیس ، احتمال موفقیت مجرمان را افزایش می دهد اگر و تنها اگر در پیشگیری از جرم ، کنترل پلیس به عنوان ورودی کاهندهدر نظر گرفته شود . این امر حتی وقتی بهره وری نهایی کنترل پلیس همواره مثبت باشد نیز صحت داشته و از طریق مخاطره اخلاقی شدید عمل می کند به کاربردهایی که این مبحث برای سیاستگذاران دارد نیز خواهیم پرداخت. کلمات کلیدی : کنترل پلیس ، جرم ، خطر اخلاقی ، ورودی های کاهنده، اقدامات امنیتی شخصی ، کالاهای همگانی
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