Results 221 to 230 of about 776,810 (287)

Hybrid Temporal Autoencoder and Similarity Matching for Low Aggregation Level Long Time Series Forecasting

Journal of Forecasting, EarlyView.
ABSTRACT Deep learning‐based long time series forecasting (LTSF) has achieved high accuracy by effectively capturing the underlying trends, seasonality, and temporal dependencies within time series data. However, at the individual entity level, termed the low aggregation level (LAL), intermittency, irregularity, and data sparsity undermine the ...
Hanbyeol Park, Sunghyun Sim, Kikun Park, Yongjae Lee, Eunhee Park, Hyerim Bae   +5 more
wiley   +1 more source

Associations Between Dietary Habits and Accelerated Aging and the Establishment of an Accelerated Aging Interpretable Risk Prediction Model via Shapley Additive Explanations: Cross-Sectional Study From Two Representative Populations. [PDF]

JMIR Aging
Wu Z, Zhang N, Wang H, Yang Y, Shen H, Zhang Q, Cao Y, Du Y, Ji D.   +8 more
europepmc   +1 more source

Beyond Prediction: Data, Baselines, Explanation, and Causation in Machine Learning for Food Insecurity

Food Safety and Health, EarlyView.
The gains from machine learning in nowcasting and forecasting food insecurity are still small and limited and cannot be observed in all countries. This review summarizes the public resources for data, corrects common misconceptions about model requirements, and establishes baseline requirements, explanations, causal inference, and equity in operational
Shabnam Mehboob, Azman Abdullah, Gunesh Kumar, Samreen Memon, Naila Afghan   +4 more
wiley   +1 more source

Research on Fuzzy Control of Methanol Distillation Based on SHAP (SHapley Additive exPlanations) Interpretability and Generative Artificial Intelligence. [PDF]

Sensors (Basel)
Gong Y, Zhang Q, Ren Y, Liu Z, Abu Seman MT.   +4 more
europepmc   +1 more source

Majorbio Cloud 2026 Update: An End‐to‐End Solution for Proteomics Research

iMetaMed, EarlyView.
The recent upgrade of Majorbio Cloud facilitates a more streamlined and accurate research process, aiding researchers across the various proteomics subfields. Furthermore, it propels the advancement of multi‐layered, multi‐omics scientific investigations centered around proteins.
Caiping Shi, Chang Han, Jichen Han, Bing Yang, Yachen Dong, Jianhua Zhao, Binxu Liu, Rundong Fang, Wenyao Fu, Jiawen Ma, Meng Luo, Lixing Feng, Yitong Feng, Huimin Cui, Mengxi Li, Huasheng Huang, Xianglin Zhang, Kegang Yu   +17 more
wiley   +1 more source

Artificial intelligence‐assisted nanozyme design for medical and environmental applications

Journal of Intelligent Medicine, EarlyView.
AI‐assisted nanozyme design integrates cross‐source data and machine learning to enable predictive structure‐activity relationships, accelerating intelligent diagnostics, precision therapeutics, and environmental surveillance. Abstract Nanozymes, a class of nanomaterials with intrinsic enzyme‐like catalytic activities, have emerged as promising ...
Xiaolin Guo, Hao Zhang, Zihan Zhao, Qingshan Liu, Jiayi Liu, Jiang Huang, Changlong Liu, Xiaoyu Mu   +7 more
wiley   +1 more source

Prediction of lymphovascular invasion in invasive breast cancer via intratumoral and peritumoral multiparametric magnetic resonance imaging machine learning-based radiomics with Shapley additive explanations interpretability analysis. [PDF]

Quant Imaging Med Surg
Chen S, Zhong Z, Chen Y, Tang W, Fan Y, Sui Y, Hu W, Pan L, Liu S, Kong Q, Guo Y, Liu W.   +11 more
europepmc   +1 more source

Early prediction of acute kidney injury in traumatic and non‐traumatic rhabdomyolysis using an interpretable machine learning model: A multicenter study with external validation

Journal of Intelligent Medicine, EarlyView.
Abstract Acute kidney injury (AKI) is a common and severe complication of rhabdomyolysis (RM), and early risk stratification remains challenging because of its multifactorial and heterogeneous nature. We developed and externally validated an interpretable machine learning (ML) model for early prediction of AKI in RM across traumatic and non‐traumatic ...
Chunli Liu, Jie Shi, Fengjuan Wang, Liang Ma, Huangang Hu, Li Zhang, Jie Song, Heng Jin, Dingwei Yang, Xiaoqin Guo, Haojun Fan, Qi Lv   +11 more
wiley   +1 more source

Optimizing Hydrogen Production in the Co-Gasification Process: Comparison of Explainable Regression Models Using Shapley Additive Explanations. [PDF]

Entropy (Basel)
Vaiyapuri T.
europepmc   +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