1,947 Results Found

Factor modeling is a popular strategy to induce sparsity in multivariate models as they scale to higher dimensions. We develop Bayesian inference for a recently proposed latent factor copula model, which utilizes a pair copula construction to couple...

A collaborative recommender system based on a latent factor model has achieved significant success in the field of personalized recommender systems. However, the latent factor model suffers from sparsity problems. It is also limited in its ability to...

In certain newly established or niche e-commerce platforms, user–item interactions are often exceedingly sparse due to limited user bases or specialized product lines, posing significant obstacles to accurate personalized recommendations. To ad...

Business process outcome prediction plays an essential role in business process monitoring. It continuously analyzes completed process events to predict the executing cases’ outcome. Most of the current outcome prediction focuses only on the ac...

Nowadays, as the number of items is increasing and the number of items that users have access to is limited, user-item preference matrices in recommendation systems are always sparse. This leads to a data sparsity problem. The latent factor analysis...

With the rapid development of the economy, car ownership has grown rapidly, which causes many traffic problems. In recent years, intelligent transportation systems have been used to solve various traffic problems. To achieve effective and efficient t...

We provide evidence on the least biased ways to identify causal effects in situations where there are multiple outcomes that all depend on the same endogenous regressor and a reasonable but potentially contaminated instrumental variable that is avail...

The implicit feedback information associated with actual behavior can symmetrically reflect consumer preference, which is valuable and deserves a deep investigation. Considering the inherent uncertainty and fuzziness of implicit data, the question of...

This paper deals with symmetrical data that can be modelled based on Gaussian distribution, such as linear mixed models for longitudinal data. The latent factor linear mixed model (LFLMM) is a method generally used for analysing changes in high-dimen...

The problem of predicting students’ performance has been recently tackled by using matrix factorization, a popular method applied for collaborative filtering based recommender systems. This problem consists of predicting the unknown performance...

In structural health monitoring (SHM), ensuring data completeness is critical for enhancing the accuracy and reliability of structural condition assessments. SHM data are prone to random missing values due to signal interference or connectivity issue...

To better understand burnout and its development, researchers have shown an increasing interest in recent years in identifying different profiles of burnout and its development process. However, there have been few longitudinal studies on the profile...

A novel methodology to model electricity prices and latent causes as endogenous, multivariate time-series is developed and is applied to the Texas energy market. In addition to exogenous factors like the type of renewable energy and system load, obse...

Background/Objectives: Cardiometabolic disease (CD) risk factors refer to the conditions that increase the likelihood of developing several health complications. The purpose of this study was to identify latent classes of CD risk factors among Brazil...

Background/Objectives: Cognitive decline is common in ageing, ranging from mild to severe manifestations. Although several modifiable risk factors have been identified, they are typically examined individually. This study aimed to identify latent pro...

The aim of this study was to identify factors associated with non-adherence to tuberculosis (TB) preventive treatment among contacts with latent TB infection for new cases of pulmonary TB cases reported in Catalonia in 2019–2021. All contacts a...

Youth victimization in schools remains a fervent public health issue, despite increased awareness of this issue, and this is especially true for marginalized populations like lesbian, gay, bisexual, transgender, and queer (LGBTQ) youth. Youth violenc...

Type 2 diabetes mellitus (T2DM) and tuberculosis (TB) together impose a high disease burden in terms of both mortality and health economics worldwide. The objective of this study was to estimate the prevalence and risk factors of latent TB infection...

Latent tuberculosis infection (LTBI) remains an important public health issue, as individuals can harbor Mycobacterium tuberculosis without symptoms and later develop active disease. This study aimed to assess the prevalence and risk factors associat...

Eating Behaviour Traits (EBTs) are psychological constructs developed to explain patterns of eating behaviour, including factors that motivate people to (over or under) eat. There is a need to align and clarify their unique contributions and harmonis...

Formal Bayesian comparison of two competing models, based on the posterior odds ratio, amounts to estimation of the Bayes factor, which is equal to the ratio of respective two marginal data density values. In models with a large number of parameters...

Conjugation of latent growth factors to superparamagnetic iron oxide nanoparticles (SPIONs) is potentially useful for magnetically triggered release of bioactive macromolecules. Thus, the goal of this work was to trigger the release of active Transfo...

Immune cell state alterations rewire HIV-1 gene expression, thereby influencing viral latency and reactivation, but the mechanisms are still unfolding. Here, using a screen approach on CD4⁺ T cell models of HIV-1 latency, we revealed Small Molecule R...

This paper introduces a new methodology to estimate time-varying alphas and betas in conditional factor models, which allows substantial flexibility in a time-varying framework. To circumvent problems associated with the previous approaches, we intro...

The dual-factor model of mental health has garnered substantial support, positing the necessity of encompassing both negative (e.g., psychological problems) and positive (e.g., well-being) indicators in comprehensive evaluations of people’s men...

Toxoplasmosis is a parasitic disease with worldwide prevalence. Despite the relatively similar effects of toxoplasmosis and smoking on alteration in neurotransmitters, especially dopamine, little is known about the relation of Toxoplasma gondii infec...

In recent years, graph neural networks (GNNS) have been demonstrated to be a powerful way to learn graph data. The existing recommender systems based on the implicit factor models mainly use the interactive information between users and items for tra...

Factor analysis is a well-known statistical method to describe the variability of observed variables in terms of a smaller number of unobserved latent variables called factors. Even though latent factors are conceptually independent of each other, th...

Optimal asset allocation is a key topic in modern finance theory. To realize the optimal asset allocation on investor’s risk aversion, various portfolio construction methods have been proposed. Recently, the applications of machine learning are...

In memory of Dr. Dennis John McFarland, who passed away recently, our objective is to continue his efforts to compare psychometric networks and latent variable models statistically. We do so by providing a commentary on his latest work, which he enco...

Tuberculous granuloma formation is mediated by hypoxia-inducible factor 1 alpha (HIF-1α), and is essential for establishing latent tuberculosis infection (LTBI) and its progression to active tuberculosis (TB). Here, we investigated whether HIF-...

Drug–drug interactions (DDIs) can pose significant risks in clinical practice and pharmacovigilance. Although traditional association rule mining techniques, such as the Apriori algorithm, have been applied to drug safety signal detection, thei...

Background: This study aims to reveal the demographic and clinical data of patients receiving TNF-α blockers, to compare the characteristics of those who received latent tuberculosis infection (LTBI) treatment and those who did not, and to eval...

Though recommendation systems can help users save time while shopping online, their performance is significantly limited by sparse user data and the inability to capture temporal dynamics of user preferences, such as interest forgetting and topic evo...

This paper studies variable selection for the data set, which has heavy-tailed distribution and high correlations within blocks of covariates. Motivated by econometric and financial studies, we consider using quantile regression to model the heavy-ta...

We propose a new Bayesian nonparametric prior for latent feature models, called the Convergent Indian Buffet Process (CIBP). We show that under the CIBP, the number of latent features is distributed as a Poisson distribution, with the mean monotonica...

Social determinants of health (SDoH) have become an increasingly important area to acknowledge and address in healthcare; however, dealing with these measures in outcomes research can be challenging due to the inherent collinearity of these factors....

One of the most important ways to improve, update, and sustain teachers’ skills in an institution is via training. Nonetheless, despite the resources invested in training, learners’ mobilization of new learning after they return to work d...

This manuscript provides a comprehensive exploration of Probabilistic latent semantic analysis (PLSA), highlighting its strengths, drawbacks, and challenges. The PLSA, originally a tool for information retrieval, provides a probabilistic sense for a...

This study aimed to analyse the classification, development trends and the influencing factors of the Chinese older adults’ mental health state. Based on longitudinal data of Chinese older adults from 2005 to 2014, 2077 older adults aged 64 to...

This study clarified the patterns of possessing modifiable risk factors of dementia that can be corrected by the elderly who were primarily determined to have mild cognitive impairment (MCI), and then determined the relationship between retention pat...

Microsporidia are opportunistic intracellular parasites, generating serious pathology in individuals with a compromised immune system. Infection by microsporidia inhibits p53 and Caspase 3, proteins involved in apoptosis and the cell cycle, which are...

The indoor environment is composed of several exposures existing simultaneously. Therefore, it might be useful to combine exposures into common combined measures when used to assess the association with health. The aim of our study was to identify pa...

In Indonesia, the implementation of tuberculosis (TB) contact investigation is limited, with low detection rates. We report the yield of and risk factors for TB disease and infection for household contacts (HHCs) investigated using chest X-ray (CXR)...

Globally, road traffic accidents are an important public health concern which needs to be tackled. A multidisciplinary approach is required to understand what causes them and to provide the evidence for policy support. In Spain, one of the roads with...

Tourists are confronted with congestion caused by concentrated travel during public holidays. In order to guide tourists to make voluntary changes regarding their travel times during holidays, this paper focuses on exploring holiday rush-hour avoidan...

Underlying pathophysiological mechanisms drive excessive clustering of cardiometabolic risk factors, causing metabolic syndrome (MetS). MetS status may transform as adolescents transition to young adulthood. This study investigated the latent cluster...

Semi-supervised non-negative matrix factorization (NMF) has achieved successful results due to the significant ability of image recognition by a small quantity of labeled information. However, there still exist problems to be solved such as the inter...

Document clustering is to group documents according to certain semantic features. Topic model has a richer semantic structure and considerable potential for helping users to know document corpora. Unfortunately, this potential is stymied on text docu...

Figural reasoning as an indicator of fluid intelligence and the domains of the Five Factor Model were explored as predictors of scholastic performance. A total of 836 Chinese secondary school students (406 girls) from grades 7 to 11 participated. Fig...