Results 231 to 240 of about 57,230 (310)

TAN-FGBMLE: Tree-Augmented Naive Bayes Structure Learning Based on Fast Generative Bootstrap Maximum Likelihood Estimation for Continuous-Variable Classification. [PDF]

Entropy (Basel)
Wei C, Zhang T, Li C, Wang P, Ye Z.
europepmc   +1 more source

Wildfire Risk Assessment of Transmission-Line Corridors Based on Naïve Bayes Network and Remote Sensing Data. [PDF]

Sensors (Basel), 2021
Chen W, Zhou Y, Zhou E, Xiang Z, Zhou W, Lu J.   +5 more
europepmc   +1 more source

Distinct Nasal Microbiome Profiles and Prediction Model for Allergic Rhinitis, Nonallergic Rhinitis, and Healthy Children

World Journal of Otorhinolaryngology - Head and Neck Surgery, EarlyView.
The alpha and beta diversity of the nasal microbiome differed among children with allergic rhinitis (AR), nonallergic rhinitis (NAR), and healthy controls (HCs). Compared to HC, AR had more Escherichia‐Shigella, Negativicoccus, and Campylobacter, while NAR had more Dolosigranulum and fewer Enterobacteriaceae.
Kantima Kanchanapoomi, Iyarit Thaipisuttikul, Perapon Nitayanon, Witchaya Srisuwatchari, Punchama Pacharn, Nualanong Visitsunthorn, Orathai Jirapongsananuruk   +6 more
wiley   +1 more source

Label dependency modeling in Multi-Label Naïve Bayes through input space expansion. [PDF]

PeerJ Comput Sci
Chitra P, Balasubramanian SB, Khattab O, Al-Kadri MO.   +3 more
europepmc   +1 more source

Accurate detection of Covid-19 patients based on Feature Correlated Naïve Bayes (FCNB) classification strategy. [PDF]

J Ambient Intell Humaniz Comput, 2022
Mansour NA, Saleh AI, Badawy M, Ali HA.
europepmc   +1 more source

Feathers and flu: identifying data gaps in avian influenza host dynamics to prioritize wildlife conservation Plumas y gripe: identificación de datos faltantes en la dinámica de hospedadores de la influenza aviar para priorizar la conservación de la vida silvestre

Wildlife Monographs, EarlyView.
We describe the host response continuum for highly pathogenic avian influenza viruses (HPAIV), including the continuum of host responses to HPAIV infection and exposure based on the primary axis of host competence, ability to infect other hosts, and host vulnerability.
Johanna A. Harvey, Matthew Gonnerman, Shenglai Yin, Cody M. Kent, Joshua Cullen, Jeffery D. Sullivan, Jonathan B. Dain, Nichola J. Hill, Diann J. Prosser, Jennifer M. Mullinax   +9 more
wiley   +1 more source

Improving Gaussian Naive Bayes classification on imbalanced data through coordinate-based minority feature mining. [PDF]

PeerJ Comput Sci
Wang W, Yan L, Liu F, Li Y.
europepmc   +1 more source

MNBC: a multithreaded Minimizer-based Naïve Bayes Classifier for improved metagenomic sequence classification. [PDF]

Bioinformatics
Lu R, Dumonceaux T, Anzar M, Zovoilis A, Antonation K, Barker D, Corbett C, Nadon C, Robertson J, Eagle SHC, Lung O, Rudar J, Surujballi O, Laing C.   +13 more
europepmc   +1 more source

Towards applying internet of things and machine learning for the risk prediction of COVID-19 in pandemic situation using Naive Bayes classifier for improving accuracy. [PDF]

Mater Today Proc, 2022
Deepa N, Sathya Priya J, Devi T.
europepmc   +1 more source

AML‐Net: Attention‐based multi‐scale lightweight model for brain tumour segmentation in internet of medical things

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Brain tumour segmentation employing MRI images is important for disease diagnosis, monitoring, and treatment planning. Till now, many encoder‐decoder architectures have been developed for this purpose, with U‐Net being the most extensively utilised. However, these architectures require a lot of parameters to train and have a semantic gap. Some
Muhammad Zeeshan Aslam, Basit Raza, Muhammad Faheem, Aadil Raza   +3 more
wiley   +1 more source