Results 51 to 60 of about 175,878 (142)

An Integrated Machine Learning Approach for Congestive Heart Failure Prediction

Diagnostics
Congestive heart failure (CHF) is one of the primary sources of mortality and morbidity among the global population. Over 26 million individuals globally are affected by heart disease, and its prevalence is rising by 2% yearly.
M. Sheetal Singh, Khelchandra Thongam, Prakash Choudhary, P. K. Bhagat   +3 more
doaj   +1 more source

Bridging the Gap: Missing Data Imputation Methods and Their Effect on Dementia Classification Performance

Brain Sciences
Background/Objectives: Missing data is a common challenge in neuroscience and neuroimaging studies, especially in the context of neurodegenerative disorders such as Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD).
Federica Aracri, Maria Giovanna Bianco, Andrea Quattrone, Alessia Sarica   +3 more
doaj   +1 more source

Optimizing GAIN model to improve AOD imputation using MODIS MAIAC data and multi-source data fusion as an example

GIScience & Remote Sensing
Aerosol Optical Depth (AOD) is a crucial parameter for monitoring air quality and studying atmosphere behavior, but satellite-based AOD measurements often suffer from significant gaps due to cloud cover and other obstructions.
Anusha Srirenganathan Malarvizhi, Phoebe Pan, Tayven Stover, Donglian Sun, Chaowei Yang   +4 more
doaj   +1 more source

Fixed sherwood duel optimization for time series imputation

IJAIN (International Journal of Advances in Intelligent Informatics)
Missing values remain a persistent challenge in time-series data, particularly within large-scale monitoring systems where reliable forecasting and evaluation are essential.
Agung Bella Putra Utama, Aji Prasetya Wibawa, Anik Nur Handayani, Andrew Nafalski   +3 more
doaj   +1 more source

Kant’s Idealized Imputation of the Propensity to Evil in Religion Within the Boundaries of Mere Reason

Religions
In Religion, Kant posits an innate and natural propensity to evil, which he implicitly designates as “radical evil”. However, this notion has been criticized for its apparent incompatibility with freedom and its problematic atemporality, leading scholars
Hui Yuan
doaj   +1 more source

mbSparse: an autoencoder-based imputation method to address sparsity in microbiome data

Gut Microbes
The involvement of gut microbiota in host physiological activities is crucial, yet the high sparsity of microbiome data, marked by numerous zeros in count matrices, presents huge analytical challenges.
Changlu Qi, Yiting Cai, Guoyou He, Kai Qian, Mian Guo, Liang Cheng   +5 more
doaj   +1 more source

Missing data imputation: focusing on single imputation.

Annals of translational medicine, 2016
Complete case analysis is widely used for handling missing data, and it is the default method in many statistical packages. However, this method may introduce bias and some useful information will be omitted from analysis. Therefore, many imputation methods are developed to make gap end. The present article focuses on single imputation.
openaire   +1 more source

SGA-DT: An adaptive fusion framework for missing data imputation and interpretable healthcare classification. [PDF]

PLoS One
Jena M, Dehuri S, Cho SB.
europepmc   +1 more source

Prior-guided factorization for reliable imputation of scRNA-seq data. [PDF]

PLoS Comput Biol
Wu Y, Xu L, Aung YW, Daoud AM.
europepmc   +1 more source

Genotype imputation performance in Nellore cattle across different SNP panels and software tools. [PDF]

Trop Anim Health Prod
Campos G, Mulim HA, Ventura H, Souza N, Cardoso F, Oliveira HR.   +5 more
europepmc   +1 more source