Results 41 to 50 of about 8,962 (250)

Clinical Significance of Therapeutic Drug Level Monitoring for Mycophenolate in Patients With Extrarenal Systemic Lupus Erythematosus—A Systematic Review and Meta‐Analysis

Arthritis Care &Research, EarlyView.
Objective Clinical response to mycophenolic acid (MPA) is highly heterogeneous; thus, therapeutic drug level monitoring (TDM) may help improve treatment efficacy. This systematic review and meta‐analysis examined therapeutic ranges for MPA levels associated with better outcomes and safety in patients with systemic lupus erythematosus (SLE ...
Zahraa Qamhieh, Dalia Sriwi, Callie Saric, Tripti Singh, Christie M. Bartels, Shivani Garg   +5 more
wiley   +1 more source

Subset Models for Multivariate Time Series Forecast

2024 IEEE 40th International Conference on Data Engineering Workshops (ICDEW)
Abstract: Multivariate time series find extensive applications in conjunction with machine learning methodologies for scenario forecasting across various domains. Nevertheless, certain domains exhibit inherent complexities and diversities, which detrimentally impact the predictive efficacy of global models.
de Freitas Saldanha, Raphael, Ribeiro, Victor, Peña, Eduardo, Pedroso, Marcel, Akbarinia, Reza, Valduriez, Patrick, Porto, Fabio   +6 more
openaire   +3 more sources

Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites

Advanced Functional Materials, EarlyView.
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou, Yunsik Ohm, Ren‐Mian Chin, Olivia Kerr, Krithika Manohar, Mohammad H. Malakooti   +5 more
wiley   +1 more source

Multivariate Financial Time-Series Prediction With Certified Robustness

IEEE Access, 2020
The futures market's forecasts are significant to investors and policymakers, where the application of deep learning approaches to finance has received a great deal of attention.
Hui Li, Yunpeng Cui, Shuo Wang, Juan Liu, Jinyuan Qin, Yilin Yang   +5 more
doaj   +1 more source

Sustainable Electrochemical Synthesis of High‐Quality MXenes: Mechanistic Insights, Applications, Challenges, and Technological Prospects

Advanced Functional Materials, EarlyView.
Electrochemical etching provides an eco‐friendly alternative to hazardous HF methods for MXene production. This approach facilitates the selective isolation of the A‐layer from MAX phases with tunable surface terminations. Controlling voltage, electrolytes, temperature, and duration enables the optimal structural integrity. Nevertheless, existing scale
Jagdeep Singh, Madhusudhana M Devadiga, Santosh K. Tiwari, AS Dhaliwal, Gurpreet Singh Selopal   +4 more
wiley   +1 more source

Multi-Scale Transformer Pyramid Networks for Multivariate Time Series Forecasting

IEEE Access
Multivariate Time Series (MTS) forecasting entails the intricate process of modeling temporal dependencies within historical data records. Transformers have demonstrated remarkable performance in MTS forecasting due to their capability to capture long ...
Yifan Zhang, Rui Wu, Sergiu M. Dascalu, Frederick C. Harris   +3 more
doaj   +1 more source

MTSMAE: Masked Autoencoders for Multivariate Time-Series Forecasting

2022 IEEE 34th International Conference on Tools with Artificial Intelligence (ICTAI), 2022
Large-scale self-supervised pre-training Transformer architecture have significantly boosted the performance for various tasks in natural language processing (NLP) and computer vision (CV). However, there is a lack of researches on processing multivariate time-series by pre-trained Transformer, and especially, current study on masking time-series for ...
Peiwang Tang, Xianchao Zhang 0002
openaire   +2 more sources

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

Advanced Materials, EarlyView.
Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Forecasting Inflation Using Univariate and Multivariate Time Series

JISR Management and Social Sciences & Economics, 2009
The purpose of the study is to forecast inflation in Pakistan from January to June 2008. This study set out to redress the deficiency and explicitly use of time series techniques solely for forecasting purposes.
Azam Ali, S.M. Husnain Bokhari
doaj  

Multivariate Segment Expandable Encoder-Decoder Model for Time Series Forecasting

IEEE Access
Accurate time series forecasting is critical in a variety of fields, including transportation, weather prediction, energy management, infrastructure monitoring, and finance.
Yanhong Li, David C. Anastasiu
doaj   +1 more source