Results 201 to 210 of about 67,939 (291)

Structural brain imaging biomarkers for predicting seizure recurrence after a first unprovoked seizure. [PDF]

Epilepsia Open
Ooi S, Tailby C, Pardoe HR, Carney PW, Sethi M, Haderlein J, Jackson GD, Vaughan DN.   +7 more
europepmc   +1 more source

Artificial intelligence‐assisted detection of epileptic spasms using electroencephalographic–video analysis

Epilepsia, EarlyView.
Abstract Objective This study was undertaken to develop and validate an artificial intelligence (AI) diagnostic tool using hybrid electroencephalographic (EEG)–video signals for automatic epileptic spasms (ES) detection. Methods This retrospective cohort study with internal cross‐validation and multicenter external validation was conducted from July ...
Lin Wan, Nan Lin, Wen Wang, Zi Liang, Yisu Dong, Haibo He, Jian Chen, Yuying Fan, Tong Liu, Hongjie Wang, Weike Cheng, Guangshuang Lu, Juan Wang, Bo Zhang, Qiang Lu, Guang Yang   +15 more
wiley   +1 more source

Explainable artificial intelligence for molecular design in pharmaceutical research. [PDF]

Chem Sci
Lamens A, Bajorath J.
europepmc   +1 more source

A Multivariate Mixed‐Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini, Shaghayegh Karimzadeh, Paulo B. Lourenço   +2 more
wiley   +1 more source

Machine learning of factors for improving oyster hatchery production. [PDF]

PLoS One
Vishwakarma S, Gray MW, Silsbe GM, Lyubchich V.   +3 more
europepmc   +1 more source

Ensemble Deep Learning–Based Wind Power Forecasting With Self‐Adaptive Osprey Optimization Algorithm

Energy Science &Engineering, EarlyView.
Design of Self‐Adaptive Osprey (SAO) algorithm: The novel SAO algorithm is designed by integrating the exploration capability of the conventional Osprey algorithm by including the self‐adaptiveness for enhancing the convergence rate. Ensemble Deep Learning for wind power forecasting: The wind forecasting is employed using the proposed Ensemble learning
Johncy Bai Johnson, Sivarani Thankamony Saradha Devi, Kumar Chandrasekaran, Sourav Barua   +3 more
wiley   +1 more source

Interpretable artificial intelligence for predicting blood transfusion after surgery for femoral shaft fractures: A retrospective analysis. [PDF]

Indian J Anaesth
Manyam R, Gupta P, Lou P, Guo R, Carro A, Heinz ER.   +5 more
europepmc   +1 more source

Smart Solar Power Site Selection Through a Hybrid Computational Framework of Neuro‐Fuzzy With Genetic Algorithm Optimization

Energy Science &Engineering, EarlyView.
Solar Power plants at various locations a: Pavagada SPP, Karnataka b: Bhadla SPP, Rajasthan c: West Bengal Solar Park ABSTRACT This paper presents a new neuro‐fuzzy multi‐criteria decision‐making (MCDM) framework designed to optimize the selection of solar power plant (SPP) sites across India.
Rajkumari Malemnganbi Devi, Benjamin A. Shimray, Ingudam Chitrasen Meitei, Khelchandra Thongam, Shuma Adhikari, Anuradha Laishram, Subir Datta, Ahmed Al Mansur, Taha Selim Ustun   +8 more
wiley   +1 more source

Prediction method for rock shear strength parameters based on data-driven and interpretability analysis. [PDF]

Sci Rep
Jin ZJ, Wang C, Qi S, Liu Y, Yu H, He ZW.   +5 more
europepmc   +1 more source

Interpretable Tree‐Based Models for Predicting Short‐Term Rockburst Risk Considering Multiple Factors

Energy Science &Engineering, EarlyView.
Interpretable tree‐based models integrate microseismic, geological, and mining indicators to predict short‐term rockburst risk. SHAP analysis reveals the dominant role of energy‐related features and clarifies nonlinear factor interactions, enabling transparent and reliable early‐warning in deep coal mines.
Shuai Chen, Linming Dou, Atao Li, Wu Cai, Lei Zhang   +4 more
wiley   +1 more source