Hasil untuk "Information technology"

Marie-Claude Boudreau, D. Robey

D. Jorgenson

Автор предлагаемой статьи Дейл Йоргенсон является одним из наиболее значимых современных экономистов. Его блестящие работы в различных областях экономики принесли ему заслуженное уважение коллег во всем мире. В своей стране профессор Д. Йоргенсон избирался председателем Американского эконометрического общества в 1987 г. В настоящее время он является президентом Американской экономической ассоциации. Значителен вклад профессора Д. Йоргенсона в воспитание молодых экономистов в знаменитых университетах: Беркли с 1959 по 1969 гг. и с 1969 г. - в Гарварде. Профессор Д. Йоргенсон любезно предоставил "Экономическому журналу ВШЭ" право опубликовать свое ежегодное обращение к членам Американской экономической ассоциации от 6 января 2001 г. Одновременно с "Экономическим журналом ВШЭ" это обращение будет напечатано в "American Economic Review" (Vol. 91, N 1, р. 1-32). Во время предстоящего визита в ГУ-ВШЭ, в середине мая 2001 г., профессор Д. Йоргенсон выступит с открытой лекцией, тема которой развивает содержание данной публикации.

E. Clemons, Sashidhar P. Reddi, M. Row

G. Stoneburner, Alice Goguen, Alexis Feringa

Gautam Ray, W. A. Muhanna, J. Barney

Curtis P. Armstrong, V. Sambamurthy

J. A. Fitzsimmons, Mona J. Fitzsimmons, Sanjeev K. Bordoloi

Anne Beaudry, A. Pinsonneault

M. Khosrow-Pour

K. Cresswell, A. Sheikh

R. Beck, M. Avital, M. Rossi et al.

E. Turban

A. Chakravarty, Rajdeep Grewal, V. Sambamurthy

A. Kellermann, Spencer S. Jones

D. Ukpabi, Heikki Karjaluoto

Kapil Sayal, Laura Wyatt, Louise Thomson et al.

Background Emotional disorders are common in children and young people and can significantly impair their quality of life. Evidence-based treatments require a timely and appropriate diagnosis. The utility of standardised diagnostic assessment tools may aid the detection of emotional disorders, but there is limited evidence of their clinical value. Objectives To assess the clinical effectiveness and cost effectiveness of a standardised diagnostic assessment for children and young people with emotional difficulties referred to Child and Adolescent Mental Health Services. A nested qualitative process evaluation aimed to identify the barriers and facilitators to using a standardised diagnostic assessment tool in Child and Adolescent Mental Health Services. Design A United Kingdom, multicentre, two-arm, parallel-group randomised controlled trial with a nested qualitative process evaluation. Setting Eight National Health Service Trusts providing multidisciplinary specialist Child and Adolescent Mental Health Services. Participants Children and young people aged 5–17 years with emotional difficulties referred to Child and Adolescent Mental Health Services, excluding emergency/urgent referrals that required an expedited assessment. In the qualitative process evaluation, 15 young people aged 16–17 years, 38 parents/carers and 56 healthcare professionals participated in semistructured interviews. Interventions Participants were randomly assigned (1 : 1) following referral receipt to intervention (the development and well-being assessment) and usual care, or usual care only. Main outcome measures Primary outcome was a clinician-made diagnosis decision about the presence of an emotional disorder within 12 months of randomisation, collected from Child and Adolescent Mental Health Services clinical records. Secondary outcomes collected from clinical records included referral acceptance, time to offer and start treatment/interventions and discharge. Data were also self-reported from participants through online questionnaires at baseline, 6 and 12 months post randomisation, and the cost effectiveness of the intervention was investigated. Results One thousand two hundred and twenty-five (1225) children and young people were randomly assigned (1 : 1) to study groups between 27 August 2019 and 17 October 2021; 615 were assigned to the intervention and 610 were assigned to the control group. Adherence to the intervention (full/partial completion of the development and well-being assessment) was 80% (494/615). At 12 months, 68 (11%) participants in the intervention group received an emotional disorder diagnosis versus 72 (12%) in the control group [adjusted risk ratio 0.94 (95% confidence interval 0.70 to 1.28); p = 0.71]. Child and Adolescent Mental Health Services acceptance of the index referral [intervention 277 (45%) vs. control 262 (43%); risk ratio: 1.06 (95% confidence interval: 0.94 to 1.19)] or any referral by 18 months [intervention 374 (61%) vs. control 352 (58%); risk ratio: 1.06 (95% confidence interval: 0.97 to 1.16)] was similar between groups. There was no evidence of any differences between groups for any other secondary outcomes. The qualitative nested process evaluation identified a number of barriers and facilitators to the use of the development and well-being assessment during the trial, particularly at the assessment and diagnosis stages of the Child and Adolescent Mental Health Services pathway. Limitations It was not possible to mask participants, clinicians or site researchers collecting source data to treatment allocation. Conclusions We found no evidence that completion of the development and well-being assessment aided the detection of emotional disorders in this study. Using the development and well-being assessment in this way cannot be recommended for clinical practice. Future research To determine longer-term service use outcomes and to investigate whether receipt of a clinical diagnosis makes a difference to clinical outcomes and care/intervention receipt. Funding This synopsis presents independent research funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme as award number 16/96/09. Plain language summary Emotional difficulties are common in children and young people, and many may be referred to Child and Adolescent Mental Health Services. Referrals are sometimes rejected because of insufficient information. Even if the referral is accepted, a clinical diagnosis is often not reached. A correct diagnosis is vital so that the right help can be offered. We investigated whether a standardised online information-gathering package (development and well-being assessment) helps with the assessment and diagnosis process in Child and Adolescent Mental Health Services. We invited children and young people and their families, following a routine (non-urgent) referral into Child and Adolescent Mental Health Services, from eight National Health Services Trusts across England. One thousand two hundred and twenty-five (1225) families took part – half received usual care (control group), and half received usual care and were also asked to complete the development and well-being assessment (development and well-being assessment group). Families also completed questionnaires about the child’s/young person’s mental health at the beginning of the study and then 6 and 12 months later. Child and Adolescent Mental Health Services clinical records were reviewed 12 and 18 months after joining the study to look at what care was offered and received through Child and Adolescent Mental Health Services. We also interviewed a range of young people, family members and staff in Child and Adolescent Mental Health Services about their views and experience of using the development and well-being assessment and the summary development and well-being assessment report. At 12-month follow-up, there was no difference in the number receiving an emotional disorder diagnosis; 11% in the development and well-being assessment group and 12% in the control group. The same was found at 18 months (14% vs. 15%). There was no difference between the groups in the time taken to reach a diagnosis or to offer or start treatment, nor was there any significant impact on whether Child and Adolescent Mental Health Services accepted the referral. The interviews showed that young people and families found the development and well-being assessment and report to be useful; however, the development and well-being assessment report was not used consistently, as intended, by clinicians during assessments to aid diagnosis. These findings show that completing the development and well-being assessment after referral into Child and Adolescent Mental Health Services did not have any impact on whether a diagnosis was made by Child and Adolescent Mental Health Services or on the care received.

Shahid Mahmood, Asifa Iqbal, Amel Ali Alhussan et al.

Abstract This study investigates the pivotal role of political stability, good governance, and institutional support in achieving Sustainable Development Goals (SDGs) 7, 11, and 12 in Pakistan, an emerging economy. SDG 7 deals with affordable, reliable, sustainable and modern energy for all, SDG 11 deals with sustainable cities and communities and SDGs 12 promotes sustainable consumption and production patterns. The data was collected using a quantitative method from various sources, including the Ministry of Planning, Development and Special Initiatives, the Ministry of Climate Change, the Pakistan Institute of Development Economics, and various NGOs involved in issues such as renewable energy, sustainable cities, and responsible consumption. The collected data was analyzed by using SMART PLS. This study concludes that political stability serves as the foundation for achieving sustainable development goals. It has been observed that the implementation of good governance, which includes principles of transparency, accountability, and public participation, significantly enhances the effectiveness of policies aimed at achieving these SDGs. More specifically, sufficient financial resources and appropriate physical infrastructure are identified as key factors in addressing challenges related to Pakistan’s sustainable development goals. Policymakers should also prioritize investments in sustainable infrastructure projects that align with SDGs 7, 11, and 12, such as investing in renewable energy sources, sustainable urban development, and promoting responsible consumption and production practices.

Muhammad Attique Khan, Usama Shafiq, Ameer Hamza et al.

Abstract Deep learning has significantly contributed to medical imaging and computer-aided diagnosis (CAD), providing accurate disease classification and diagnosis. However, challenges such as inter- and intra-class similarities, class imbalance, and computational inefficiencies due to numerous hyperparameters persist. This study aims to address these challenges by presenting a novel deep-learning framework for classifying and localizing gastrointestinal (GI) diseases from wireless capsule endoscopy (WCE) images. The proposed framework begins with dataset augmentation to enhance training robustness. Two novel architectures, Sparse Convolutional DenseNet201 with Self-Attention (SC-DSAN) and CNN-GRU, are fused at the network level using a depth concatenation layer, avoiding the computational costs of feature-level fusion. Bayesian Optimization (BO) is employed for dynamic hyperparameter tuning, and an Entropy-controlled Marine Predators Algorithm (EMPA) selects optimal features. These features are classified using a Shallow Wide Neural Network (SWNN) and traditional classifiers. Experimental evaluations on the Kvasir-V1 and Kvasir-V2 datasets demonstrate superior performance, achieving accuracies of 99.60% and 95.10%, respectively. The proposed framework offers improved accuracy, precision, and computational efficiency compared to state-of-the-art models. The proposed framework addresses key challenges in GI disease diagnosis, demonstrating its potential for accurate and efficient clinical applications. Future work will explore its adaptability to additional datasets and optimize its computational complexity for broader deployment.

Min Pei, Jianke Yu, Chen Chen et al.

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