Results 81 to 90 of about 4,586 (136)

Machine learning-based prediction of preterm birth risk using methylation changes in neonatal cord blood CpG sites. [PDF]

BMC Pregnancy Childbirth
Feng Y, Ni Y, Wang W, Guo F, Wang L, Zhu F, Zhang L, Feng Y.   +7 more
europepmc   +1 more source

A Commentary on Chatterjee Et Al. (2018): A Corrected Framework for Group Sparsity in Zero-Inflated Negative Binomial Models. [PDF]

Stat Med
Iqbal A, Mallick H, Ogundimu EO.
europepmc   +1 more source

Uncertainty quantification in high-dimensional linear models incorporating graphical structures with applications to gene set analysis. [PDF]

Bioinformatics
Tan X, Tan X, Zhang X, Cui Y, Liu X.
europepmc   +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

Exploring an EM-algorithm for banded regression in computational neuroscience. [PDF]

Imaging Neurosci (Camb)
Fuglsang SA, Madsen KH, Puonti O, Siebner HR, Hjortkjær J.   +4 more
europepmc   +1 more source

Variable selection in mixture cure models using elastic net penalty: application to COVID-19 data. [PDF]

PLoS One
Ramalata A, Adekpedjou A, Lesaoana M.
europepmc   +1 more source

Omics feature selection with the extended SIS R package: identification of a body mass index epigenetic multimarker in the Strong Heart Study. [PDF]

Am J Epidemiol
Domingo-Relloso A, Feng Y, Rodriguez-Hernandez Z, Haack K, Cole SA, Navas-Acien A, Tellez-Plaza M, Bermudez JD.   +7 more
europepmc   +1 more source

A Machine Learning-Based Prediction Model for Diabetic Kidney Disease in Korean Patients with Type 2 Diabetes Mellitus. [PDF]

J Clin Med
Lee KA, Kim JS, Kim YJ, Goak IS, Jin HY, Park S, Kang H, Park TS.   +7 more
europepmc   +1 more source

James-Stein Estimator Improves Accuracy and Sample Efficiency in Human Kinematic and Metabolic Data. [PDF]

Ann Biomed Eng
Alwan A, Srinivasan M.
europepmc   +1 more source

A Comprehensive Review of Numerical and Machine Learning Approaches for Predicting Concrete Properties: From Fresh to Long-Term. [PDF]

Materials (Basel)
Adsul N, Choi Y, Kang ST.
europepmc   +1 more source