Category: Machine Learning

Dataset The dataset used in this study originates from a retrospective cohort of residents from four DomusVi nursing homes in Spain. Ethical approval for the study was granted by the relevant institutional committee (Code: 2023/576). The database contains information from 2,608 residents and includes 4,718,828 activity records collected over a 13-year period (2011–2024). Each entry […]

Avinash, B. S., Srisupattarawanit, T. & Ostermeyer, H. Numerical methods for information tracking of noisy and non-smooth data in large-scale statistics. J. Eng. Res. Rep. https://doi.org/10.9734/jerr/2019/v6i416957 (2019). Article  Google Scholar  Zhang, J. et al. Guest editorial learning from noisy multimedia data. IEEE Trans. Multimed https://doi.org/10.1109/TMM.2022.3159014 (2022). Article  Google Scholar  Arain, Z., Iliodromiti, S., Slabaugh, G., […]

Vos T, Lim SS, Abbafati C, Abbas KM, Abbasi M, Abbasifard M, et al. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: a systematic analysis for the Global Burden of Disease Study 2019. The Lancet. 2020;396:1204–22. Article  Google Scholar  Herrman H, Patel V, Kieling C, Berk M, Buchweitz C, Cuijpers […]

Genon, S., Eickhoff, S. B. & Kharabian, S. Linking interindividual variability in brain structure to behaviour. Nat. Rev. Neurosci. 23, 307–318 (2022). Article  CAS  PubMed  Google Scholar  Sui, J., Jiang, R., Bustillo, J. & Calhoun, V. Neuroimaging-based individualized prediction of cognition and behavior for mental disorders and health: methods and promises. Biol. Psychiatry 88, 818–828 […]

Relationship between NO₂ and meteorological parameters The relationship between NO₂ concentrations and meteorological variables revealed distinct nonlinear dependencies, as captured by all the four algorithms used. Figure 4 presents the predicted versus observed NO₂ concentrations using all seven meteorological parameters. Among the models, the RF and GB algorithms demonstrated superior predictive capability, while the DT and […]

Niroomandi, S., Alfaro, I., Gonzalez, D., Cueto, E., Chinasta, F. Real-time simulation of surgery using low-order modeling and X-FEM technology. internal. J. Number. Method Biomed. engineering 28574–588 (2012). Google Scholar Kuiper, W., Milde, A., Volkwein, S. Reduced Order Modeling (ROM) for Simulation and Optimization: Powerful Algorithms as a Key Enabler for Scientific Computing (Springer, 2018). […]

Case study Taiwan’s water quality monitoring system was selected as the case study for this research due to its comprehensiveness and relevance to water resource management in the region. The system is managed by Taiwan’s Environmental Protection Administration and covers rivers, reservoirs, and lakes nationwide, focusing on assessing, reporting, and improving water quality66. Taiwan is […]

To address this challenge, a comprehensive and validated database is the first step in data-driven modeling of radiation effects in polymers. A new IAEA Coordination Research Project (CRP) entitled Data-Driven Prediction of Radiation-Induced Structural Changes in Polymers aims to address this gap. The 5-year CRP will create a validated database of polymer-radiation interactions through a […]

Sign up now and see the future Don’t miss innovations from the cutting edge of science and technology Back in 2017, China’s State Council released the first draft of its long-term AI strategy in a comprehensive policy document. The report declares that by 2030, China needs to develop its “AI industry competitiveness” to “world-leading levels”, […]

to evidential deep learning (EDL), a framework for one-shot quantification of epistemic and aleatoric uncertainty. More specifically, we will focus on a subset: deep evidential regression (DER) as published in Amini et al. 2020. Don’t worry if these words are confusing, we will walk through them shortly. This article assumes some prior experience with machine […]