Results 141 to 150 of about 42,250 (218)

Generalized Additive Model With Dynamic Coefficients for Spatiotemporal Ozone Predictions

Environmetrics, Volume 37, Issue 3, April 2026.
ABSTRACT Accurate prediction of surface‐level ozone concentrations is critical for air quality management and public health protection. This study develops a flexible spatiotemporal statistical modeling framework to predict daily mean O3 concentrations across Italy by integrating satellite‐derived ozone estimates with ground‐based observations and high‐
Abdollah Jalilian, Claudia Cappello, Monica Palma, Sandra De Iaco   +3 more
wiley   +1 more source

Deep Quake Dynamics: A Multimodal Fault‐Aware Approach to Earthquake Magnitude and Occurrence Time Forecasting

Geoscience Data Journal, Volume 13, Issue 2, April 2026.
EQMT integrates earthquake catalog data, fault‐network geometry, engineered features, and graph embeddings in a unified framework for forecasting earthquake magnitude and occurrence time. The framework is designed to reflect inter‐fault spatial dependencies together with temporal seismic patterns, addressing limitations of approaches based only on ...
Kiymet Kaya, Murat Sahin, Furkan Mangir, Alp Baris Beydemir, Cenk Yaltirak, Sule Gunduz Oguducu   +5 more
wiley   +1 more source

Utilizing and Optimizing Forecasting Models for Nursing Demand: A Narrative Review

Health Science Reports, Volume 9, Issue 4, April 2026.
ABSTRACT Background Accurately forecasting nursing demand is essential for effective workforce planning in the context of increasing patient volumes and the growing complexity of healthcare systems. Reliable forecasting supports optimal staffing, enhances patient care quality, and reduces operational risks.
Kalpana Singh, Liyan Ajit D. Souza, Ananth Nazarene, Amane Mounia, Mahmoud Abdelwahab Khedr, Ahmad Mousa, Rebecca Rejo George, Abdulqadir J. Nahwan   +7 more
wiley   +1 more source

Climate‐Driven Advanced Machine Learning Approach for Dengue Incidence Forecasting in Bangladesh

Health Science Reports, Volume 9, Issue 4, April 2026.
ABSTRACT Background and Aims Dengue fever has become a significant and an increasing public health menace in Bangladesh. Despite the abundance of research on the dengue outbreaks, the majority of the studies are limited by the short‐term time frame of research, a narrow scope, or to one modeling methodology.
Omar Faruk
wiley   +1 more source

Machine learning versus traditional formulas for fetal weight estimation: An international multicenter study evaluating prediction accuracy across birth weight percentiles

International Journal of Gynecology &Obstetrics, Volume 173, Issue 1, Page 456-462, April 2026.
Abstract Objective To assess whether machine learning (ML) offers improved birth weight prediction accuracy, since despite numerous models, the Hadlock formula remains the clinical standard. Methods A multicenter retrospective study analyzed data from 9674 singleton pregnancies with estimated fetal weight (EFW) within 7 days of delivery.
Omer Dor, Eran Ashwal, May Cohen, Ori Rottenstreich, Yariv Yogev, Noam Shomron, Misgav Rottenstreich   +6 more
wiley   +1 more source

Redefining multi-target weather forecasting with a novel deep learning model: Hierarchical temporal convolutional long short-term memory with attention (HTC-LSTM-Attn) in Bangladesh. [PDF]

PLoS One
Kabir MA, Chakma C.
europepmc   +1 more source

FORECASTING EXCHANGE RATE :A Uni-variate out of sample Approach [PDF]

In this paper we tried to build univariate model to forecast exchange rate of Indian Rupee in terms of different currencies like SDR, USD, GBP, Euro and JPY. Paper uses Box-Jenkins Methodology of building ARIMA model.
Mahesh Kumar Tambi
core  

Weibull‐Neural Network Framework for Wind Turbine Lifetime Monitoring and Disturbance Identification

Wind Energy, Volume 29, Issue 4, April 2026.
ABSTRACT Wind turbines are vital for sustainable energy, yet their reliability under diverse operational and environmental conditions remains a challenge, often leading to costly failures. This study presents a novel Weibull‐Neural Network Framework to enhance wind turbine lifetime monitoring by estimating reliability (R(t)) and mean residual life (MRL)
Fatemeh Kiadaliry, Sadigh Raissi, Alireza Rashidi Komijan   +2 more
wiley   +1 more source

Validity of Galaxy Watch for Estimating Energy Expenditure During Intermittent Running: Cross-Sectional Study. [PDF]

JMIR Form Res
Ferreira ARP, Inoue A, Barbosa RLM, Hayek C, Reis M, Alcântara JA, Shigueoka AH, Dos Santos MR.   +7 more
europepmc   +1 more source

Artificial intelligence streamlines scientific discovery of drug–target interactions

British Journal of Pharmacology, Volume 183, Issue 8, Page 1673-1690, April 2026.
Abstract Drug discovery is a complicated process through which new therapeutics are identified to prevent and treat specific diseases. Identification of drug–target interactions (DTIs) stands as a pivotal aspect within the realm of drug discovery and development. The traditional process of drug discovery, especially identification of DTIs, is marked by
Yuxin Yang, Feixiong Cheng
wiley   +1 more source