Results 111 to 120 of about 283,042 (193)

The impact of imputation quality on machine learning classifiers for datasets with missing values. [PDF]

Commun Med (Lond), 2023
Shadbahr T, Roberts M, Stanczuk J, Gilbey J, Teare P, Dittmer S, Thorpe M, Torné RV, Sala E, Lió P, Patel M, Preller J, AIX-COVNET Collaboration, Rudd JHF, Mirtti T, Rannikko AS, Aston JAD, Tang J, Schönlieb CB.   +18 more
europepmc   +1 more source

Anna: an open-source platform for real-time integration of machine learning classifiers with veterinary electronic health records. [PDF]

BMC Vet Res
Kong CY, Vasquez P, Farhoodimoghadam M, Brandt C, Brown TC, Reagan KL, Zwingenberger A, Keller SM.   +7 more
europepmc   +1 more source

Machine learning classifiers and associations of cognitive performance with hippocampal subfields in amnestic mild cognitive impairment. [PDF]

Front Aging Neurosci, 2023
Feng Q, Wang L, Tang X, Ge X, Hu H, Liao Z, Ding Z.   +6 more
europepmc   +1 more source

Detecting automobile insurance fraud using a novel penalty-driven feature selection method with particle swarm optimization and machine learning classifiers. [PDF]

Sci Rep
Özaltın Ö, Erdemir ÖK.
europepmc   +1 more source

Publisher Correction: Predicting coronary heart disease with advanced machine learning classifiers for improved cardiovascular risk assessment. [PDF]

Sci Rep
Rehman MU, Naseem S, Butt AUR, Mahmood T, Khan AR, Khan I, Khan J, Jung Y.   +7 more
europepmc   +1 more source

A Framework for Comparison and Interpretation of Machine Learning Classifiers to Predict Autism on the ABIDE Dataset. [PDF]

Hum Brain Mapp
Dong Y, Batalle D, Deprez M.
europepmc   +1 more source

Automated Boundary Identification for Machine Learning Classifiers

Proceedings of the 17th ACM/IEEE International Workshop on Search-Based and Fuzz Testing
Felix Dobslaw, Robert Feldt
openaire   +1 more source

Sex Estimation Based on Tooth Measurements on Panoramic Radiographs with Classical and Machine-Learning Classifiers. [PDF]

Front Dent
Talebi S, Fallahzadeh H, Jambarsang S, Ezoddini Ardakani F.   +3 more
europepmc   +1 more source

Evaluating the factors influencing accuracy, interpretability, and reproducibility in the use of machine learning classifiers in biology to enable standardization. [PDF]

Sci Rep
Martinez KM, Wilding K, Llewellyn TR, Jacobsen DE, Montoya MM, Kubicek-Sutherland JZ, Batni S, Manore C, Mukundan H.   +8 more
europepmc   +1 more source

Fine-Tuned Machine Learning Classifiers for Diagnosing Parkinson's Disease Using Vocal Characteristics: A Comparative Analysis. [PDF]

Diagnostics (Basel)
Meral M, Ozbilgin F, Durmus F.
europepmc   +1 more source