Results 181 to 190 of about 31,305 (267)

Inter‐Material Transfer Learning for Accelerated Nanofluid Heat Transfer Prediction: A Machine Learning Approach for Energy Systems

Energy Science &Engineering, EarlyView.
This study presents an inter‐material transfer learning framework for nanofluid heat transfer prediction in energy systems. By leveraging knowledge from Al2O3‐water data, the model accurately predicts hybrid Al2O3‐TiO2 nanofluid performance with only 20 simulations, achieving R2 = 0.985 and reducing computational requirements by 78. ABSTRACT This paper
Soumaya Hadj Salah, Aymen Ochi, Sonia Bezi   +2 more
wiley   +1 more source

Evaluating the liver fibrosis and waist-to-height ratio(LFWHR) as a gallstone disease predictor: a nomogram model and SHAP analysis. [PDF]

Sci Rep
Zhao Y, Wang F, Zhang GY, Bie YK, Feng YB, Wang FT.   +5 more
europepmc   +1 more source

Tree‐Boost–Guided CNN–BiLSTM–Transformer for Solar Irradiance Forecasting: Cross‐Regional Evidence for Sustainable Energy Planning

Energy Science &Engineering, EarlyView.
This graphical abstract illustrates a reproducible pipeline that combines gradient‐boosting‐based feature selection with a CNN–BiLSTM–Transformer model to forecast solar irradiance across multi‐site satellite and ground datasets, delivering robust, high‐accuracy predictions that support sustainable grid planning and reliable PV integration.
Muhammad Farhan Hanif, Usama Hassan, Javid Hussain, Irfan Ali Khan, Yuldasheva Gulora, Syed Masood Arif Bukhari   +5 more
wiley   +1 more source

Development of a clinical prediction model for inflammatory biomarkers and enlarged basal ganglia perivascular spaces using SHAP analysis: feature selection and model interpretation. [PDF]

Front Neurol
Lv J, Gao D, Yong W, Yu W, Wang L, Ma S, Li H, Zhang S, Guo Z, Yan H, Ju Z, Liu Y, Wu L, Guo X.   +13 more
europepmc   +1 more source

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models

Journal of Forecasting, EarlyView.
ABSTRACT Predicting carbon allowance prices has grown more crucial in relation to carbon market regulation, financial strategy, and environmental policy development. This study examines a hybrid forecasting system that combines deep learning with ensemble machine learning models to forecast the price fluctuations of EU Emissions Allowance (EUAs) within
Saptarshi Ganguly, Pooja Sengupta, Divya Aggarwal   +2 more
wiley   +1 more source

Atherogenic index of plasma and risk of acute kidney injury in critically ill patients: a multi-cohort study with machine learning and SHAP analysis. [PDF]

Ren Fail
Li DM, Yu F, Xia W, Jiang MH, Yang LJ, Yang HY, Yin SJ, Wang P, Meng R, Cun SH, Yang HN, Du PN, Wang Y, He GH.   +13 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

Integrating SHAP analysis with machine learning to predict postpartum hemorrhage in vaginal births. [PDF]

BMC Pregnancy Childbirth
Song Z, Lin H, Shao M, Wang X, Chen X, Zhou Y, Zhang D.   +6 more
europepmc   +1 more source

Precision Mapping of Retinal Disease: Identification of Differential Progression Trajectories via Imaging Phenomics

iMetaMed, EarlyView.
Applying single‐cell RNA‐seq techniques to large‐scale clinical phenotypic data enables the discovery of differential disease progression trajectories and the construction of data‐driven progression scores. These can then be integrated into precision medicine studies to investigate the drivers of patient‐specific disease outcomes. ABSTRACT We propose a
Christian Anderson, Liam Scott, Irene Leung, Ferenc Sallo, Catherine Egan, Tunde Peto, The MacTel Consortium, Melanie Bahlo, Martin Friedlander, Simone Tzaridis, Lea Scheppke, Roberto Bonelli   +11 more
wiley   +1 more source

Machine learning-based prediction model for intraoperative hypothermia risk in thoracoscopic lobectomy patients: A SHAP analysis. [PDF]

Medicine (Baltimore)
Chen R, Ma X, Liu M, Deng X, Wei F, Li G, Luo S.   +6 more
europepmc   +1 more source