Results 91 to 100 of about 1,104 (139)

Anomaly detection of hyperspectral images based on improved isolation forest algorithm. [PDF]

Sci Rep
Li A.
europepmc   +1 more source

Outliers and anomalies in training and testing datasets for AI-powered morphometry-evidence from CT scans of the spleen. [PDF]

Front Artif Intell
Vasilev Y, Pamova A, Bobrovskaya T, Vladzimirskyy A, Omelyanskaya O, Astapenko E, Kruchinkin A, Vladimir N, Arzamasov K.   +8 more
europepmc   +1 more source

EODA: A three-stage efficient outlier detection approach using Boruta-RF feature selection and enhanced KNN-based clustering algorithm. [PDF]

PLoS One
Kumar S, Varshney S, Jain U, Johri P, Almazyad AS, Mohamed AW, Hosseinzadeh M, Shokouhifar M.   +7 more
europepmc   +1 more source

The Signal in the Extreme: A Systematic Outlier Framework Identifies Discrete Immunometabolic Subtypes in Human and Cellular Models. [PDF]

Med Sci (Basel)
Garcia-Coste JJ, Aguayo-Cerón KA, Espinosa-Raya J, García-Rivero AA, López-Leyva C, Gutiérrez-Rojas RA, Vargas-De-León C, Romero-Nava R.   +7 more
europepmc   +1 more source

Machine learning-based strategies for improving healthcare data quality: an evaluation of accuracy, completeness, and reusability. [PDF]

Front Artif Intell
Jarmakovica A.
europepmc   +1 more source

DNA methylation biomarkers-based pan-cancer classifier: predictive modeling for cancer classification. [PDF]

Genome Med
Bińkowski J, Wojdacz TK.
europepmc   +1 more source

Intrusion detection with HACDT-Net and TRBM-Net using a hybrid deep learning framework with enhanced sampling techniques. [PDF]

Sci Rep
Padma Priya N, Mohanbabu G.
europepmc   +1 more source

Early damage detection in bridges using a variational autoencoder-based hybrid unsupervised learning framework. [PDF]

Sci Rep
Pakzad SS, Masoodi AR.
europepmc   +1 more source

Anomaly-based threat detection in smart health using machine learning. [PDF]

BMC Med Inform Decis Mak
Tabassum M, Mahmood S, Bukhari A, Alshemaimri B, Daud A, Khalique F.   +5 more
europepmc   +1 more source

Advancing computational evaluation of adsorption via porous materials by artificial intelligence and computational fluid dynamics. [PDF]

Sci Rep
Mhohamdi H, Altimari US, Vaghela K, Vivek V, Hota S, Singh D, Manchanda M, Shomurotova S, Tomar P, Alam MM.   +9 more
europepmc   +1 more source