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1دورية أكاديمية
المؤلفون: Gholi Zadeh Kharrat, Fatemeh, Gagne, Christian, Lesage, Alain, Gariépy, Geneviève, Pelletier, Jean-François, Brousseau-Paradis, Camille, Rochette, Louis, Pelletier, Eric, Lévesque, Pascale, Mohammed, Mada, Wang, JianLi
المساهمون: Jain, Lakshit, New Frontiers for Research Funds grant from TriAgency Institutional Programs Secretariat, Quebec Suicide, mood and associated disorders research network
المصدر: PLOS ONE ; volume 19, issue 4, page e0301117 ; ISSN 1932-6203
الوصف: Suicide is a complex, multidimensional event, and a significant challenge for prevention globally. Artificial intelligence (AI) and machine learning (ML) have emerged to harness large-scale datasets to enhance risk detection. In order to trust and act upon the predictions made with ML, more intuitive user interfaces must be validated. Thus, Interpretable AI is one of the crucial directions which could allow policy and decision makers to make reasonable and data-driven decisions that can ultimately lead to better mental health services planning and suicide prevention. This research aimed to develop sex-specific ML models for predicting the population risk of suicide and to interpret the models. Data were from the Quebec Integrated Chronic Disease Surveillance System (QICDSS), covering up to 98% of the population in the province of Quebec and containing data for over 20,000 suicides between 2002 and 2019. We employed a case-control study design. Individuals were considered cases if they were aged 15+ and had died from suicide between January 1st, 2002, and December 31st, 2019 (n = 18339). Controls were a random sample of 1% of the Quebec population aged 15+ of each year, who were alive on December 31st of each year, from 2002 to 2019 (n = 1,307,370). We included 103 features, including individual, programmatic, systemic, and community factors, measured up to five years prior to the suicide events. We trained and then validated the sex-specific predictive risk model using supervised ML algorithms, including Logistic Regression (LR), Random Forest (RF), Extreme Gradient Boosting (XGBoost) and Multilayer perceptron (MLP). We computed operating characteristics, including sensitivity, specificity, and Positive Predictive Value (PPV). We then generated receiver operating characteristic (ROC) curves to predict suicides and calibration measures. For interpretability, Shapley Additive Explanations (SHAP) was used with the global explanation to determine how much the input features contribute to the models’ output and the ...
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2دورية أكاديمية
المؤلفون: Boniel-Nissim, Meyran, Tynjälä, Jorma, Gobiņa, Inese, Furstova, Jana, van den Eijnden, Regina J.J.M., Marino, Claudia, Klanšček, Helena Jeriček, Klavina-Makrecka, Solvita, Villeruša, Anita, Lahti, Henri, Vieno, Alessio, Wong, Suzy L., Villberg, Jari, Inchley, Joanna, Gariépy, Geneviève
المساهمون: Leerstoel Stevens, Youth in Changing Cultural Contexts
مصطلحات موضوعية: Adolescents, HBSC, International survey, Sleep, Social media, Health(social science), Neuropsychology and Physiological Psychology, Social Sciences (miscellaneous), Behavioral Neuroscience
الوصف: Objective: Over the past decade, concurrent with increasing social media use (SMU), there has been a shift toward poorer sleep among adolescents in many countries. The purpose of this study was to examine the cross-national associations between adolescent SMU and sleep patterns, by comparing 4 different categories of SMU (nonactive, active, intense, and problematic use). Design, setting, and participants: Data were from 86,542 adolescents in 18 European and North American countries that participated in the 2017/18 Health Behaviour in School-aged study. Measurements: Mixed-effects linear regression models were used to examine cross-national associations between 4 SMU categories and adolescent sleep duration, bedtime and social jetlag derived from self-reported data. Results: For all countries combined, nonactive SMU was associated with longer sleep, earlier bedtimes, and less social jetlag, compared to active SMU, although the differences were minor. By comparison, intense and problematic SMU were associated with less sleep and later bedtimes on both school and nonschool days, and greater social jetlag, compared to active SMU. While findings were relatively consistent between countries, some differences were observed, suggesting that the national and cultural context may be important in interpreting results. Conclusions: These findings suggest that both intense and problematic SMU are associated with poorer sleep patterns in adolescents across most countries. Further research is needed to identify effective policies, programs, and messaging to promote the healthy use of social media and prevent potential negative impacts on adolescent sleep.
وصف الملف: application/pdf
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3دورية أكاديمية
المؤلفون: Morningstar, Brandon, Clayborne, Zahra, Wong, Suzy L., Roberts, Karen C., Prince, Stephanie A., Gariépy, Geneviève, Goldfield, Gary S., Janssen, Ian, Lang, Justin J.
المساهمون: public health agency of canada, Public Health Agency of Canada
المصدر: Canadian Journal of Public Health ; volume 114, issue 4, page 642-650 ; ISSN 0008-4263 1920-7476
مصطلحات موضوعية: Public Health, Environmental and Occupational Health, General Medicine
الوصف: Objective To determine the association between social media use (SMU) and physical activity (PA) among Canadian adolescents. Methods We used data from 12,358 participants in grades 6 to 10 who responded to the Canadian component of the 2017/2018 Health Behaviour in School-aged Children (HBSC) survey. Social media intensity and problematic SMU were assessed using a 4-point mutually exclusive scale that contained three categories based on intensity (non-active, active, and intense SMU) and one category based on the presence of addiction-like symptoms irrespective of intensity (problematic SMU). PA was assessed for five domains (i.e., school curriculum, organized sport, exercise, outdoor play, and active transport) and dichotomized using the first quartile to represent high PA engagement in each domain. Meeting PA recommendation of 60 min per day of moderate-to-vigorous PA was calculated using the sum of the five domains. Logistic regression models were used to assess the association between SMU and PA, with active SMU used as the reference group for all models. Results Non-active SMU was associated with lower odds of meeting the daily PA recommendations and of high engagement in all five domains of PA when compared to active SMU. Intense SMU was associated with higher odds of meeting the daily PA recommendations. Problematic SMU was not associated with meeting daily PA recommendations, but it was significantly associated with lower odds of high PA engagement in the exercise domain. Conclusion The findings of this study suggest that non-active SMU was significantly associated with lower PA levels. Problematic SMU was only significantly associated with lower PA levels in the exercise domain. Intense SMU was associated with higher odds of meeting the PA recommendation.
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4دورية أكاديمية
المؤلفون: Graham, Eva, Gariépy, Geneviève, Orpana, Heather
المصدر: Health Research Policy and Systems ; volume 21, issue 1 ; ISSN 1478-4505
مصطلحات موضوعية: Health Policy
الوصف: Aims Depression is a disease driven by dynamic processes both at the individual- and system-level. System dynamics (SD) models are a useful tool to capture this complexity, project the future prevalence of depression and understand the potential impact of interventions and policies. SD models have been used to model infectious and chronic disease, but rarely applied to mental health. This scoping review aimed to identify population-based SD models of depression and report on their modelling strategies and applications to policy and decision-making to inform research in this emergent field. Methods We searched articles in MEDLINE, Embase, PsychInfo, Scopus, MedXriv, and abstracts from the System Dynamics Society from inception to October 20, 2021 for studies of population-level SD models of depression. We extracted data on model purpose, elements of SD models, results, and interventions, and assessed the quality of reporting. Results We identified 1899 records and found four studies that met the inclusion criteria. Studies used SD models to assess various system-level processes and interventions, including the impact of antidepressant use on population-level depression in Canada; the impact of recall error on lifetime estimates of depression in the USA; smoking-related outcomes among adults with and without depression in the USA; and the impact of increasing depression incidence and counselling rates on depression in Zimbabwe. Studies included diverse stocks and flows for depression severity, recurrence, and remittance, but all models included flows for incidence and recurrence of depression. Feedback loops were also present in all models. Three studies provided sufficient information for replicability. Conclusions The review highlights the usefulness of SD models to model the dynamics of population-level depression and inform policy and decision-making. These results can help guide future applications of SD models to depression at the population-level.
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5دورية أكاديمية
المؤلفون: Wang, JianLi, Gholi Zadeh Kharrat, Fatemeh, Pelletier, Jean-François, Rochette, Louis, Pelletier, Eric, Lévesque, Pascale, Massamba, Victoria, Brousseau-Paradis, Camille, Mohammed, Mada, Gariépy, Geneviève, Gagné, Christian, Lesage, Alain
المساهمون: Tri-Agency Institutional Programs Secretariat, Government of Canada, Canada Research Chairs
المصدر: BMJ Open ; volume 13, issue 2, page e066423 ; ISSN 2044-6055 2044-6055
مصطلحات موضوعية: General Medicine
الوصف: Introduction Suicide has a complex aetiology and is a result of the interaction among the risk and protective factors at the individual, healthcare system and population levels. Therefore, policy and decision makers and mental health service planners can play an important role in suicide prevention. Although a number of suicide risk predictive tools have been developed, these tools were designed to be used by clinicians for assessing individual risk of suicide. There have been no risk predictive models to be used by policy and decision makers for predicting population risk of suicide at the national, provincial and regional levels. This paper aimed to describe the rationale and methodology for developing risk predictive models for population risk of suicide. Methods and analysis A case–control study design will be used to develop sex-specific risk predictive models for population risk of suicide, using statistical regression and machine learning techniques. Routinely collected health administrative data in Quebec, Canada, and community-level social deprivation and marginalisation data will be used. The developed models will be transformed into the models that can be readily used by policy and decision makers. Two rounds of qualitative interviews with end-users and other stakeholders were proposed to understand their views about the developed models and potential systematic, social and ethical issues for implementation; the first round of qualitative interviews has been completed. We included 9440 suicide cases (7234 males and 2206 females) and 661 780 controls for model development. Three hundred and forty-seven variables at individual, healthcare system and community levels have been identified and will be included in least absolute shrinkage and selection operator regression for feature selection. Ethics and dissemination This study is approved by the Health Research Ethnics Committee of Dalhousie University, Canada. This study takes an integrated knowledge translation approach, involving knowledge users from ...
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6تقرير
مصطلحات موضوعية: Computer Science - Computer Vision and Pattern Recognition, Physics - Instrumentation and Detectors
الوصف: A remote-sensing system that can determine the position of hidden objects has applications in many critical real-life scenarios, such as search and rescue missions and safe autonomous driving. Previous work has shown the ability to range and image objects hidden from the direct line of sight, employing advanced optical imaging technologies aimed at small objects at short range. In this work we demonstrate a long-range tracking system based on single laser illumination and single-pixel single-photon detection. This enables us to track one or more people hidden from view at a stand-off distance of over 50~m. These results pave the way towards next generation LiDAR systems that will reconstruct not only the direct-view scene but also the main elements hidden behind walls or corners.
الوصول الحر: http://arxiv.org/abs/1703.02124Test
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7تقرير
المؤلفون: Wilson, Kali, Little, Bethany, Gariepy, Genevieve, Henderson, Robert, Howell, John, Faccio, Daniele
مصطلحات موضوعية: Physics - Optics, Physics - Atomic Physics, Quantum Physics
الوصف: Slow-light media are of interest in the context of quantum computing and enhanced measurement of quantum effects, with particular emphasis on using slow-light with single photons. We use light-in-flight imaging with a single photon avalanche diode camera-array to image in situ pulse propagation through a slow light medium consisting of heated rubidium vapour. Light-in-flight imaging of slow light propagation enables direct visualisation of a series of physical effects including simultaneous observation of spatial pulse compression and temporal pulse dispersion. Additionally, the single-photon nature of the camera allows for observation of the group velocity of single photons with measured single-photon fractional delays greater than 1 over 1 cm of propagation.
Comment: 6 pages, 5 figures, 2 supplemental moviesالوصول الحر: http://arxiv.org/abs/1611.01041Test
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8تقرير
المؤلفون: Bolduc, Eliot, Gariepy, Genevieve, Leach, Jonathan
مصطلحات موضوعية: Quantum Physics
الوصف: In quantum mechanics, predictions are made by way of calculating expectation values of observables, which take the form of Hermitian operators. It is far less common to exploit non-Hermitian operators to perform measurements. Here, we show that the expectation values of a particular set of non-Hermitian matrices, which we call column operators, directly yield the complex coefficients of a quantum state vector. We provide a definition of the state vector in terms of measurable quantities by decomposing the column operators into observables. The technique we propose renders very-large-scale quantum states significantly more accessible in the laboratory, as we demonstrate by experimentally characterising a 100 000-dimensional entangled state. This represents an improvement of two orders of magnitude with respect to previous characterisations of discrete entangled states. Furthermore, in numerical studies, we consider mixed quantum states and show that for purities greater that 0.81, we can reliably extract the most significant eigenvector of the density matrix with a probability greater than 99%. We anticipate that our method will prove to be a useful asset in the quest for understanding and manipulating large-scale quantum systems.
الوصول الحر: http://arxiv.org/abs/1506.00851Test
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9تقرير
المؤلفون: Gariepy, Genevieve, Tonolini, Francesco, Henderson, Robert, Leach, Jonathan, Faccio, Daniele
مصطلحات موضوعية: Physics - Optics, Physics - Instrumentation and Detectors
الوصف: The ability to know what is hidden around a corner or behind a wall provides a crucial advantage when physically going around the obstacle is impossible or dangerous. Previous solutions to this challenge were constrained e.g. by their physical size, the requirement of reflective surfaces or long data acquisition times. These impede both the deployment of the technology outside the laboratory and the development of significant advances, such as tracking the movement of large-scale hidden objects. We demonstrate a non-line-of-sight laser ranging technology that relies upon the ability, using only a floor surface, to send and detect light that is scattered around an obstacle. A single-photon avalanche diode (SPAD) camera detects light back-scattered from a hidden object that can then be located with centimetre precision, simultaneously tracking its movement. This non-line-of-sight laser ranging system is also shown to work at human length scales, paving the way for a variety of real-life situations.
الوصول الحر: http://arxiv.org/abs/1503.01699Test
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10دورية أكاديمية
المؤلفون: Wang, JianLi, Kharrat, Fatemeh Gholi Zadeh, Gariépy, Geneviève, Gagné, Christian, Pelletier, Jean-François, Massamba, Victoria Kubuta, Lévesque, Pascale, Mohammed, Mada, Lesage, Alain
المصدر: JMIR Public Health Surveill ; ISSN:2369-2960 ; Volume:10
مصطلحات موضوعية: Canada, Quebec, adolescent, adolescents, anxiety, case-control, depression, development, female, health administrative data, male, mental health, population risk prediction, prevention, suicide, suicide prevention, teen, teenager, teenagers, teens, validation
الوصف: Suicide is a significant public health issue. Many risk prediction tools have been developed to estimate an individual's risk of suicide. Risk prediction models can go beyond individual risk assessment; one important application of risk prediction models is population health planning. Suicide is a result of the interaction among the risk and protective factors at the individual, health care system, and community levels. Thus, policy and decision makers can play an important role in suicide prevention. However, few prediction models for the population risk of suicide have been developed.
