Results 171 to 180 of about 1,472,159 (288)

Comparison of machine learning methods for prediction of venous thromboembolism among hospitalized adults

Journal of Hospital Medicine, EarlyView.
Abstract Background Hospital‐acquired venous thromboembolism (HA‐VTE) is a significant cause of morbidity and mortality among hospitalized adults. Accurate prediction of HA‐VTE is crucial for timely intervention and prevention. While logistic regression is widely used for the development of clinical prediction models, there is ongoing interest in the ...
Yeji Ko, Benjamin French, Jonathan S. Schildcrout, Merna El‐Rifai, Adam Wright, Benjamin F. Tillman, Amanda S. Mixon, Henry J. Domenico   +7 more
wiley   +1 more source

Downscaling of Temperatures Over the Eastern Mediterranean for the 21st Century

International Journal of Climatology, EarlyView.
We developed an analogue‐based statistical downscaling method, using a K‐nearest‐neighbour framework, to project daily maximum temperature (Tmax) and minimum temperature (Tmin) at 32 homogenized meteorological stations. Late twenty‐first‐century (2080–2100) temperature projections obtained using the method, show robust warming across all stations and ...
Anton Gelman, Lidiya Shendrik, Efrat Morin, Chaim I. Garfinkel, Dorita Rostkier‐Edelstein   +4 more
wiley   +1 more source

Cloud native design of IoT baseband functions : Introduction to cloud native principles

, 2020
The exponential growth of research and deployment of 5G networks has led to an increased interest in massive Machine Type Communications (mMTC), as we are on the quest to connect all devices. This can be attributed to the constant development of long-distance and low-powered Internet-of- Things (IoT) technologies, or, Low Power Wide Area Network (LPWAN)
openaire   +1 more source

Satellite and Reanalysis Dataset Dependence of ETCCDI Extreme Precipitation Trends in Paraná, Southern Brazil

International Journal of Climatology, EarlyView.
Extreme precipitation trends detected in Paraná, Southern Brazil (1983–2024), are strongly conditioned by the dataset used, with reanalyses indicating coherent inland drying and longer dry spells, observations retaining stronger mesoscale heterogeneity, and satellite products often showing declines in short‐duration extremes. Monthly diagnostics reveal
Paulo Miguel de Bodas Terassi, Jakeline Baratto, Vitor Hugo Rosa Biffi   +2 more
wiley   +1 more source

Lightning Pose: improved animal pose estimation via semi-supervised learning, Bayesian ensembling and cloud-native open-source tools. [PDF]

Nat Methods
Biderman D, Whiteway MR, Hurwitz C, Greenspan N, Lee RS, Vishnubhotla A, Warren R, Pedraja F, Noone D, Schartner MM, Huntenburg JM, Khanal A, Meijer GT, Noel JP, Pan-Vazquez A, Socha KZ, Urai AE, International Brain Laboratory, Cunningham JP, Sawtell NB, Paninski L.   +20 more
europepmc   +1 more source

Machine Learning‐Based Correction of Reanalysis Surface Radiation Fluxes Using Ground‐Measured Data in the Southern Brazilian Pampa Biome

International Journal of Climatology, EarlyView.
This study demonstrates that ERA5 provides more accurate surface radiation flux estimates than MERRA2 across the Southern Brazilian Pampa. Machine learning models, particularly Random Forest, further improved the precision of reanalysis data for climate applications.
Olusola Samuel Ojo, Michel Baptistella Stefanello, Alecsander Mergen, Maria Eduarda Oliveira Pinheiro, Vanessa de Arruda Souza, Débora Regina Roberti   +5 more
wiley   +1 more source

Intercomparison of a Regional Climate Model Ensemble for Selected European Catchments

International Journal of Climatology, EarlyView.
This study analyzes a regional climate model ensemble for water cycle and water resource research with two models. Results show that ICON generally outperforms TSMP1 simulations, mainly with 2‐m temperature and precipitation. These findings serve as a baseline evaluation that shows how key structural differences influence the model skill.
Jane Leonor Roque, Francis Da Silva Lopes, Julian Alberto Giles, Benjamin D. Gutknecht, Bernd Schalge, Yikui Zhang, Marco Ferro, Petra Friederichs, Klaus Goergen, Stefan Poll, Arianna Valmassoi   +10 more
wiley   +1 more source

Spatio‐Temporal Analysis of Human Thermal Comfort and Relationships With Large‐Scale Climate Indices Along Ghana's Coastal‐Urban Corridor From 1980 to 2020

International Journal of Climatology, EarlyView.
Four decades of UTCI data show increasing thermal stress along Ghana's coastal‐urban corridor, with very strong heat‐stress days rising by about 1.4 days/year. Random Forest–SHAP analysis with temporal validation identified AOD as the strongest model‐based predictor of monthly UTCI variability, followed by TSA, WHWP, and AMO.
Kwadwo Frimpong, Layin Zhu, Kathleen Baker, Israel Orimoloye   +3 more
wiley   +1 more source

The Bridge of Hope: Mediating the Relationship Between Mindfulness and Loneliness

The Journal of Humanistic Counseling, EarlyView.
ABSTRACT This cross‐sectional study sought to explore hope as a mediator between mindfulness and loneliness and social connectedness by using a structural equation modeling data analysis approach to analyze the relationships. Among a sample of 676 interpersonal trauma experiencers recruited online from a crowdsourcing platform, hope fully mediated the ...
Daniel Gutierrez, Margaret M. Poandl, Emily Kitching   +2 more
wiley   +1 more source

Common‐Mode Rejection Shifted‐Excitation Raman Difference Spectroscopy (CMR‐SERDS) Preserves Broad Structure Predictive of Soil Organic Carbon

Journal of Raman Spectroscopy, EarlyView.
Common‐mode rejection (CMR) is introduced as a physics‐motivated preprocessing method for shifted excitation Raman difference spectroscopy (SERDS) that removes the shared background of paired measurements while preserving the noncommon excitation‐dependent component. Applied to more than 900 North American soil samples, CMR improves soil organic carbon
Mahsa Zarei, Miayan Larose, Natalia V. Solomatova, Sadegh Shokatian, Edward Grant   +4 more
wiley   +1 more source