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Comparison of principal component analysis algorithms for imputation in agrometeorological data in high dimension and reduced sample size.
PLoS One
December 2024
São Paulo State University (Unesp), School of Sciences and Engineering, Tupã, São Paulo, Brasil.
Meteorological data acquired with precision, quality, and reliability are crucial in various agronomy fields, especially in studies related to reference evapotranspiration (ETo). ETo plays a fundamental role in the hydrological cycle, irrigation system planning and management, water demand modeling, water stress monitoring, water balance estimation, as well as in hydrological and environmental studies. However, temporal records often encounter issues such as missing measurements.
View Article and Find Full Text PDFCost-Effectiveness of rTMS as a Next Step in Antidepressant Non-Responders: A Randomized Comparison With Current Antidepressant Treatment Approaches.
Acta Psychiatr Scand
December 2024
Center for Economic Evaluation, Trimbos Institute - Netherlands Institute of Mental Health and Addiction, Utrecht, The Netherlands.
Background: Although repetitive transcranial magnetic stimulation (rTMS) is an effective and commonly used treatment option for treatment-resistant depression, its cost-effectiveness remains much less studied. In particular, the comparative cost-effectiveness of rTMS and other treatment options, such as antidepressant medication, has not been investigated.
Methods: An economic evaluation with 12 months follow-up was conducted in the Dutch care setting as part of a pragmatic multicenter randomized controlled trial, in which patients with treatment-resistant depression were randomized to treatment with rTMS or treatment with the next pharmacological step according to the treatment algorithm.
Applying machine learning-based multiple imputation methods to nonparametric multiple comparisons in longitudinal clinical studies.
J Biopharm Stat
December 2024
Department of Biostatistics, School of Medicine, Hacettepe University, Ankara, Turkey.
Dependent samples, in which repeated measurements are made on the same subjects, eliminate potential differences among the subjects. In k-dependent samples, missing data can occur for various reasons. The Skillings-Mack test is used instead of the Friedman test for k-dependent samples with missing observations that are non-normally distributed.
View Article and Find Full Text PDFUsing UMAP for Partially Synthetic Healthcare Tabular Data Generation and Validation.
Sensors (Basel)
December 2024
Intelligent Data Science and Artificial Intelligence Research Center, Technical University of Catalonia, Nexus II Building, Jordi Girona 29, 08034 Barcelona, Spain.
In healthcare, vast amounts of data are increasingly collected through sensors for smart health applications and patient monitoring or diagnosis. However, such medical data often comprise sensitive patient information, posing challenges regarding data privacy, and are resource-intensive to acquire for significant research purposes. In addition, the common case of lack of information due to technical issues, transcript errors, or differences between descriptors considered in different health centers leads to the need for data imputation and partial data generation techniques.
View Article and Find Full Text PDFMultiple imputation methods: a case study of daily gold price.
PeerJ Comput Sci
September 2024
Department of Mathematics, Al-Hussein Bin Talal University, Maan, Maan, Jordan.
Data imputation strategies are necessary to address the prevalent difficulty of missing values in data observation and recording operations. This work utilizes diverse imputation methods to forecast and complete absent values inside a financial time-series dataset, specifically the daily prices of gold. The predictive accuracy of imputed data is assessed in comparison to the original entire dataset to ensure its robustness.
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