COVID-19 continues to challenge health-care systems and ICUs around the globe more than one year into the pandemic and in spite of all advances in diagnosis and treatment of the disease caused by the novel SARS-CoV-2. Many open questions remain concerning optimal medical therapy, respiratory management and resource allocation, particuly in times of limited available health care personell. In the following short article, we summarized current knowlegde on management of COVID-19 in the ICU.
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| http://dx.doi.org/10.1055/a-1449-4995 | DOI Listing |
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Review of upper extremity passive joint impedance identification in people with Duchenne Muscular Dystrophy.
J Neuroeng Rehabil
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Department of BioMechanical Engineering, Delft University of Technology, Mekelweg 2, Delft, 2628 CD, South-Holland, The Netherlands.
Duchenne Muscular Dystrophy (DMD) progressively leads to loss of limb function due to muscle weakness. The incurable nature of the disease shifts the focus to improving quality of life, including assistive supports to improve arm function. Over time, the passive joint impedance (Jimp) of people with DMD increases.
View Article and Find Full Text PDFSpecialized pediatric palliative care in Italy: where are we going? The Palliped 2022-2023 study.
Ital J Pediatr
January 2025
Polistudium SRL, Milan, Italy.
Background: The PalliPed project is a nationwide, observational, cross-sectional study designed with the aim of providing a constantly updated national database for the census and monitoring of specialized pediatric palliative care (PPC) activities in Italy. This paper presents the results of the first monitoring phase of the PalliPed project, which was developed through the PalliPed 2022-2023 study, to update current knowledge on the provision of specialized PPC services in Italy.
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Statistical models versus machine learning approach for competing risks in proctological surgery.
Updates Surg
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Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy.
Clinical risk prediction models are ubiquitous in many surgical domains. The traditional approach to develop these models involves the use of regression analysis. Machine learning algorithms are gaining in popularity as an alternative approach for prediction and classification problems.
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J Clin Nurs
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The Cheryl Spencer Department of Nursing, Faculty of Social Welfare and Health Sciences, University of Haifa, Haifa, Israel.
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Real-Time On-Device Continual Learning Based on a Combined Nearest Class Mean and Replay Method for Smartphone Gesture Recognition.
Sensors (Basel)
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Department of Artifcial Intelligence, Chung-Ang University, Heukseok-dong, Dongjak-gu, Seoul 06974, Republic of Korea.
Sensor-based gesture recognition on mobile devices is critical to human-computer interaction, enabling intuitive user input for various applications. However, current approaches often rely on server-based retraining whenever new gestures are introduced, incurring substantial energy consumption and latency due to frequent data transmission. To address these limitations, we present the first on-device continual learning framework for gesture recognition.
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