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Increased Fracture Risk After Bariatric Surgery: a Case-Controlled Study with a Long-Term Follow-Up
Published 2022“…The median duration for time to fracture was 4.17 years for the surgical group and 6.09 years for controls (p-value = 0.097). …”
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Preoperative Bevacizumab Does Not Significantly Increase Postoperative Complication Rates in Patients Undergoing Hepatic Surgery for Colorectal Cancer Liver Metastases
Published 2008“…Conclusion Neither the use of BV nor timing of BV administration was associated with an increase in complication rates. …”
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Increased Frequency of Severe Hypoglycemia with the Modified-Release Gliclazide Compared to Glimepiride in Diabetic Older Adults; Propensity Score-Adjusted Analysis
Published 2022“…The risk of SHEA (Adjusted Odds Ratio AOR 6.74, p=0.002), falls (AOR 1.43, p=0.003), fractures (AOR 1.43, p=0.01), CVEA (AOR 1.66, p< 0.001), recurrent ED admission (AOR 1.39, p=0.002) were significantly higher. At the same time, documented hypoglycemia was insignificantly higher (AOR 1.17, p= 0.444) with gliclazide MR compared to glimepiride. …”
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Effective non-intrusive load monitoring of buildings based on a novel multi-descriptor fusion with dimensionality reduction
Published 2020“…This paper presents an efficient non-intrusive load monitoring framework that consists of the following main components: (i) a novel fusion of multiple time-domain features is proposed to extract appliance fingerprints; (ii) a dimensionality reduction scheme is introduced to be applied to the fused time-domain features, which relies on fuzzy-neighbors preserving analysis based QR-decomposition. …”
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Temporal self-attention for risk prediction from electronic health records using non-stationary kernel approximation
Published 2024“…However, in practice, a patient’s visits are irregularly spaced over a relatively long period of time, and disease progression patterns exhibit non-stationarity. …”
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Towards electric digital twin grid: Technology and framework review
Published 2023“…Electric Digital Twin grid can perform online analysis of the grid in real-time and integrates all the past and present data and express the current grid status to the producers and consumers and also predicts the future grid status. …”
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Learning Spatiotemporal Latent Factors of Traffic via Regularized Tensor Factorization: Imputing Missing Values and Forecasting
Published 2019“…In this article, we investigate the problem of missing data or noisy information in the context of real-time monitoring and forecasting of traffic congestion for road networks in a city. …”
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Exendin-4 promotes GSIS without increasing β-cell number through upregulation of glucose-sensing apparatus and mitochondrial oxidative phosphorylation machinery genes in hPSC-deriv...
Published 2023“…</p> <p>Conclusion: Our data demonstrated for the first time in 3D differentiation of hPSC-derived β-cells that addition of Exendin-4 promotes GSIS through upregulation of both glucose-sensing apparatus and mitochondrial oxidative phosphorylation machinery genes without increasing β-cell number.…”
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Enhancing Healthcare Systems With Deep Reinforcement Learning: Insights Into D2D Communications and Remote Monitoring
Published 2024“…In this context, Deep Reinforcement Learning (DRL) emerges as a technological advancement that improves the healthcare by enabling smart, adaptive, and real-time decision-making processes. Existing DRL applications in resource allocation, however, face significant challenges. …”
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Blockchain-Based Local Energy Market Enabling P2P Trading: An Australian Collated Case Study on Energy Users, Retailers and Utilities
Published 2022“…Moreover, the margins of both energy retailers and distribution utilities are kept unchanged or increased to some extent by the proposed trading model to incorporate them in the LEM framework effectively. …”
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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms
Published 2025“…A key requirement in these applications is minimizing the latency of data processing, particularly for time-sensitive tasks like image classification of IIoT device data. …”
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Surgical Management of Hepatic Benign Disease: Have the Number of Liver Resections Increased in the Era of Minimally Invasive Approach? Analysis from the I Go MILS (Italian Group o...
Published 2020“…During the same period, 3713 liver resections (open + MILS) were performed and 407 (11.0%) were for BD. A time-trend analysis showed that the total number of MILS and the number of MILS for malignant disease significantly increased, but this increasing trend was not documented for the number of MILS for BD, which remained stable during the study period of time. …”
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Cognitive Load Estimation Using a Hybrid Cluster-Based Unsupervised Machine Learning Technique
Published 2024“…<p dir="ltr">The increasing prevalence of non-invasive, portable Electroencephalography (EEG) sensors for neuro-physiological measurements has propelled EEG-based assessments of cognitive load (CL) into the spotlight. …”
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Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval
Published 2024“…For a large-sized data set, KPCA’s execution time and occupied storage space will increase drastically and the monitoring performance can also be affected in this case. …”
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Is board compensation excessive?
Published 2017“…For companies that overpay, the average excess compensation is greater than $60,000 per director, while directors that are underpaid receive about $33,000 less than predicted. …”
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The impact of maternal care on child development
Published 2019“…Results show that treated children enjoy an increase of 3.6 h per week in the time they spend with their mothers, mainly due to a decrease in the time spent in non-institutional care. …”
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