Results 191 to 200 of about 72,345 (262)

Predicting intradialytic exercise intolerance in maintenance hemodialysis patients: an interpretable machine learning approach integrating functional assessments. [PDF]

Ren Fail
Zhang F, Yan L, Yang Y, Yu C, Peng Y, Wang Y.   +5 more
europepmc   +1 more source

A Closed‐Loop Human Resource Management Framework for Energy Efficiency: Integrating Predictive Optimization With Behavioral Implementation

Energy Science &Engineering, EarlyView.
The proposed framework operates as a continuous cycle: organizational data streams feed into predictive optimization, which generates energy efficiency targets. These targets are translated into behavioral directives through human resource management mechanisms.
Huang Juan, Aimi Binti Anuar
wiley   +1 more source

Applying explainable artificial intelligence to interpret supervised ensemble learning models for robust credit card fraud detection. [PDF]

Sci Rep
Awad SS, Hamza AA, Sobh MA, Bahaa-Eldin AM.   +3 more
europepmc   +1 more source

Daily Residential Natural Gas Demand Forecasting Using Machine Learning Regression: Comparative Evaluation With a Case Study in Qazvin Province, Iran

Energy Science &Engineering, EarlyView.
This graphical abstract summarizes the proposed framework for improving short‐term residential natural gas consumption forecasting by integrating a novel socioeconomic indicator, the subscription growth ratio (SGR), with conventional meteorological variables.
Ali Pirzad, Mostafa Khanzadi
wiley   +1 more source

Predicting unfavorable tuberculosis outcomes using machine learning: a prospective cohort. [PDF]

Trop Med Health
Lee T, Choi I, Lee H, Kim HW, Lee EG, Park Y, Jung SS, Kim JW, Oh JY, Lee H, Kim SH, Kim SH, Lyu J, Kwon SJ, Jeong YJ, Koo HK, Kim JS, Min J.   +17 more
europepmc   +1 more source

A Comprehensive Review of AI‐Powered Energy Systems

Energy Science &Engineering, EarlyView.
The role of Artificial Intelligence (AI) in developing next‐generation energy systems is getting more day by day. Therefore, incorporating AI enables real‐time decision‐making and advanced grid management, which are essential for optimizing the use of intermittent renewable sources like wind and solar power.
Armin Razmjoo, Pedram Asef, Masoumeh Javadi, Mousa Marzband, Shady S. Refaat, Muhyaddin Rawa   +5 more
wiley   +1 more source

Machine learning-based risk prediction of overt hepatic encephalopathy after transjugular intrahepatic portosystemic shunt in patients with cirrhosis: a cohort study. [PDF]

Front Med (Lausanne)
Song L, Qiao X, Gao L, Sun Y, Feng D, Yang H.   +5 more
europepmc   +1 more source

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

Machine Learning-Based Prediction Model for 30-Day Emergency Department Revisits in a Medically Underserved Tertiary Hospital: Formative Retrospective Cohort Study. [PDF]

JMIR Form Res
Sun K.
europepmc   +1 more source