Retracted: An Intelligent and Reliable Hyperparameter Optimization Machine Learning Model for Early Heart Disease Assessment Using Imperative Risk Attributes. [PDF]
Healthcare Engineering JO.
europepmc +1 more source
ABSTRACT Interpreting the impedance response of perovskite solar cells (PSCs) is challenging due to the complex coupling of ionic and electronic motion. While drift‐diffusion (DD) modelling is a reliable method, its mathematical complexity makes directly extracting physical parameters from experimental data infeasible.
Mahmoud Nabil +4 more
wiley +1 more source
Be aware of overfitting by hyperparameter optimization! [PDF]
Tetko IV, van Deursen R, Godin G.
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Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
Machine Learning Prediction of Road Performance of Cold Recycled Mix Asphalt with Genetic Algorithm Hyperparameter Optimization. [PDF]
Wu Z +6 more
europepmc +1 more source
ABSTRACT This paper examines the determinants of generative AI (GenAI) knowledge and usage among agricultural extension professionals. Drawing on survey data from agricultural extension personnel in Tennessee, we employ regression analyses and latent Dirichlet allocation (LDA) for topic modeling of open‐ended responses to study the knowledge and usage ...
Abdelaziz Lawani +3 more
wiley +1 more source
Fraudulent account detection in social media using hybrid deep transformer model and hyperparameter optimization. [PDF]
Shukla PK +5 more
europepmc +1 more source
Hyperparameter Optimization of a Convolutional Neural Network Model for Pipe Burst Location in Water Distribution Networks. [PDF]
Antunes A +3 more
europepmc +1 more source
Threshold‐optimized machine learning models using routine clinical and laboratory data in 623 adults undergoing appendectomy. Logistic regression (AUC = 0.765) and random forest (AUC = 0.785) were the best‐performing models for appendicitis detection and complicated appendicitis prediction, respectively.
Ivan Males +8 more
wiley +1 more source
Deep learning based SentiNet architecture with hyperparameter optimization for sentiment analysis of customer reviews. [PDF]
Madhurika B, Malleswari DN.
europepmc +1 more source

