Results 161 to 170 of about 91,735 (266)

Data‐Driven Design of Scalable Perovskite Film Fabrication via Machine Learning–Guided Processing

Carbon Energy, EarlyView.
Considering complex process parameters and poor reproducibility in perovskite thin film fabrication, this study uses machine learning to analyze and predict high‐dimensional process variables. The Random Forest model, identified as the most effective, can effectively analyze and rapidly predict optimal process parameters from extensive data.
Hong Liu, Kangyan Liu, Biao Zhang, Ziang Chen, Yi Yang, Qiang Sun, Tao Ye, Bed Poudel, Kai Wang, Congcong Wu   +9 more
wiley   +1 more source

Electric vehicles charging stations load forecasting based on hybrid XGBoost-BiLSTM model. [PDF]

Sci Rep
Mansour HSE, Mohamed AS, Abdel-Aziz M.
europepmc   +1 more source

Profiling Social Entrepreneurship Orientation Through Machine Learning Predictive Modeling

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT This study examines the prediction of Social Entrepreneurship Orientation (SEO) in youth using machine learning techniques to generate a robust predictive model. Drawing on a large cross‐country survey of European youth, results indicate that cognitive–attitudinal indicators—such as concern for environmental goals, purpose‐driven motivation ...
Ángel Peiró‐Signes, Colin Donaldson, Marival Segarra‐Oña   +2 more
wiley   +1 more source

Innovative statistical method for longitudinal and hierarchical data modeling: the GMEXGBoost method. [PDF]

BMC Med Res Methodol
Asadi F, Homayounfar R, Mehrali Y, Masci C, Zayeri F.   +4 more
europepmc   +1 more source

Bridging Theory and Prediction: A Hybrid SEM and Machine Learning Approach to Optimize Lean Construction for Megaproject Sustainability in China

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Construction megaprojects, large‐scale, complex, and capital‐intensive, are particularly prone to inefficiencies, cost overruns, delays, and environmental degradation due to fragmented workflows, stakeholder misalignment, and resource intensity.
Abdelazim Ibrahim, Tarek Zayed, Zoubeir Lafhaj, Ahmed Maged, Ahmed Farouk Kineber, Jingchao Yang   +5 more
wiley   +1 more source

Using Machine Learning to Predict Adverse Events in Patients Undergoing Transcatheter Left Atrial Appendage Occlusion. [PDF]

JACC Adv
Faridi KF, Mortazavi BJ, Huang S, Zimmerman S, Friedman DJ, Khera R, Krumholz HM, Curtis JP, Freeman JV.   +8 more
europepmc   +1 more source

Left ventricular function improvement during angiotensin receptor–neprilysin inhibitor treatment in a cohort of HFrEF/HFmrEF patients

ESC Heart Failure, Volume 12, Issue 2, Page 1151-1165, April 2025.
Prediction of LVEF improvement in patients with HFrEF and HFmrEF following treatment with Sacubitril/Valsartan. Workflow of this study investigating the functional capacity improvement in response to Sacubitrail/Valsartsan in a real‐world scenario of heart failure treatment.
Florian Appenzeller, Tobias Harm, Manuel Sigle, Parwez Aidery, Klaus‐Peter Kreisselmeier, Livia Baas, Andreas Goldschmied, Meinrad Paul Gawaz, Karin Anne Lydia Müller   +8 more
wiley   +1 more source

A bio inspired hybrid optimization framework for efficient real time malware detection. [PDF]

Sci Rep
Abualhaj MM, Al-Mimi H, Al-Zyoud M, Al-Khatib SN, Daoud MS, Al-Aqrabi H, Anbar M, Shalaldeh A.   +7 more
europepmc   +1 more source

An algorithm for seizure detection in rodents

Epilepsia Open, EarlyView.
Abstract Objective Epilepsy animal research often relies on long‐term intracranial electroencephalographic (iEEG) recordings. Here, we describe an artificial neural network (ANN) algorithm for automatic detection of seizures. Methods The algorithm was trained on iEEG recordings of three mouse models of chronic epilepsy: (1) the pilocarpine model of ...
Lyna Kamintsky, Gerben van Hameren, Itai Weissberg, Pooyan Moradi, Ofer Prager, Alaa Abu Ahmad, Lior Schori, Albert Becker, Yaniv Zigel, Alon Friedman   +9 more
wiley   +1 more source

Development of a machine learning model for hepatic steatosis screening using non-invasive Traditional Chinese Medicine diagnostics and clinical variables: a health checkup study with community screening potential. [PDF]

Front Med (Lausanne)
Zhu K, Li L, Zhao Z, Zheng S, Lin B, Tang W, Li W.   +6 more
europepmc   +1 more source