Results 181 to 190 of about 1,043 (255)

Nowcasting World Trade With Machine Learning: A Three‐Step Approach

Journal of Forecasting, EarlyView.
ABSTRACT We nowcast world trade using machine learning, distinguishing between tree‐based methods (random forest and gradient boosting) and their linear‐regression‐based counterparts (macroeconomic random forest and gradient boosting—linear). While much less used in the literature, the latter are found to outperform not only the tree‐based techniques ...
Menzie Chinn, Baptiste Meunier, Sebastian Stumpner   +2 more
wiley   +1 more source

Robust Cancer Biomarker Identification From Matched Transcriptomic Data Via Bootstrapped Regularized Conditional Logistic Regression. [PDF]

Cancer Inform
Wang JH, Wu ZH, Lu HC, Guo TY.
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

Exploring variations in potential carbon and nitrogen mineralization in managed grasslands among the diversity of soils in North Carolina

Grassland Research, EarlyView.
Under steady–state conditions, potential nitrogen mineralization in soil under grasslands is closely tied to potential carbon mineralization. This study provides supporting evidence that field–specific nitrogen fertilizer recommendations could be indicated by using a simple and rapid analysis of soil–test biological activity.
Alan J. Franzluebbers
wiley   +1 more source

Prediction Modeling With Many Correlated and Zero-Inflated Predictors: Assessing the Nonnegative Garrote Approach. [PDF]

Stat Med
Gregorich M, Kammer M, Mischak H, Heinze G.   +3 more
europepmc   +1 more source

Early Feasibility of Registration of Micro‐PET/CT Scans to Annotated 3D Specimen Models

Head &Neck, EarlyView.
ABSTRACT Background Intraoperative 18F‐fluorodeoxyglucose (18F‐FDG) micro‐positron emission tomography/computed tomography (micro‐PET/CT) is an emerging modality for margin assessment. Prior to clinical use, micro‐PET/CT margin distances must be correlated with gold‐standard histopathology.
Joaquin Austerlitz, Andreja Radevic, Ashtyn McAdoo, Kyrionna Golliday, Cheng Ye, Daniel Fabbri, Adam J. Rosenberg, Marcus Balanky, Anas Alabkaa, Kim A. Ely, Mitra Mehrad, Spencer Roark, Eben Rosenthal, Michael C. Topf   +13 more
wiley   +1 more source

Modified sparse regression to solve heterogeneity and hybrid models for increasing the prediction accuracy of seaweed big data with outliers. [PDF]

Sci Rep
Ibidoja OJ, Shan FP, Ali MKM.
europepmc   +1 more source

Machine Learning‐Based Estimation of Reference Evapotranspiration and Crop Coefficients for Wheat Under Diverse Climatic Conditions

Irrigation and Drainage, EarlyView.
ABSTRACT Accurate estimation of reference evapotranspiration (ET0) and crop coefficients (Kc) is critical for irrigation planning, particularly in data‐limited regions where agriculture dominates freshwater consumption. Although machine learning (ML) methods have been widely applied to ET0 and Kc estimation, most studies address these parameters ...
Ilker Angin, Hasan Er, Mete Yaganoglu, Muhammed Sungur Demir, Abdullah Muratoglu   +4 more
wiley   +1 more source

A Method for Estimating Fluorescence Emission Spectra from the Image Data of Plant Grain and Leaves Without a Spectrometer. [PDF]

J Imaging
Tominaga S, Nishi S, Ohtera R, Sakai H.
europepmc   +1 more source

Integrating Prostate‐Specific Antigen Density and Prostate Imaging Reporting and Data System Scores to Optimize Detection of Clinically Significant Prostate Cancer: A Multivariable Risk Model Approach

Journal of Clinical Laboratory Analysis, EarlyView.
For the detection of clinically significant prostate cancer, incorporating PSA density into PI‐RADS‐based assessment improved clinical net benefit compared with PI‐RADS alone. The addition of DRE and age to this combined model produced only marginal further gain, indicating that most of the incremental clinical value was derived from PSA density rather
Yunus Kayali
wiley   +1 more source