6,436 Results Found

Software defect prediction technology can effectively improve software quality. Depending on the code metrics, machine learning models are built to predict potential defects. Some researchers have indicated that the size metric could cause confoundin...

Background: Adequate control for confounding is key to many observational study designs. Confounders are often identified based on subject matter knowledge from empirical investigations. Negative confounders, which typically generate type 2 error, i....

Software defect prediction technology can effectively detect potential defects in the software system. The most common method is to establish machine learning models based on software metrics for prediction. However, most of the prediction models are...

Sample size calculation for adequate power analysis is critical in optimizing RNA-seq experimental design. However, the complexity increases for directly estimating sample size when taking into consideration confounding covariates. Although a number...

Optical brain monitoring techniques, including near-infrared spectroscopy (NIRS), diffuse correlation spectroscopy (DCS), and photoplethysmography (PPG) have gained attention for their non-invasive, affordable, and portable nature. These methods offe...

Background/Objectives: Precautionary health behaviours (PHBs), such as hand-washing or self-isolation, are non-pharmaceutical interventions used to reduce SARS-CoV-2 transmission. We investigated the potential confounding by PHBs of COVID-19 vaccine...

Controlling for confounding bias is crucial in causal inference. Causal inference using data from observational studies (e.g., electronic health records) or imperfectly randomized trials (e.g., imperfect randomization or compliance) requires accounti...

Confounding adjustment is important for observational studies to derive valid effect estimates for inference. Despite the theoretical advancement of confounding selection procedure, it is often challenging to distinguish between confounders and media...

Confounding factors in olfactory aroma data, such as high humidity levels, substantially affect sensor outputs, masking subtle volatile organic compound (VOC) patterns and hindering generalizable machine learning models. Traditional representation le...

Timeseries forecasting plays an important role in many applications where knowledge of the future behaviour of a given quantity of interest is required. Traditionally, this task is approached using methods such as exponential smoothing, ARIMA and, mo...

Objectives: Fruit and vegetable (FV) consumption has been inversely associated with cardiovascular disease, but questions remain about the extent to which these results are due to confounding. Methods: From 2006–2010, >0.5 million adults age...

The aim of our study is to utilise longitudinal data to explore if the association between the retail fast food environment and overweight in adolescents is confounded by neighbourhood deprivation. Data from the Millennium Cohort Study for England we...

Proinflammatory biomarkers have been increasingly used in epidemiologic and intervention studies over the past decades to evaluate and identify an association of systemic inflammation with cardiovascular diseases. Although there is a strong correlati...

This paper provides a methodology to better understand the relationships between different aspects of vocal fold motion, which are used as features in machine learning-based approaches for detecting respiratory infections from voice recordings. The r...

Several meta-analyses have found a positive association between a popular type of “fad diet”, ketogenic diets, and their effect on anthropometric and blood parameters. However, the non-specific inclusion criteria for meta-analyses may lead to incorre...

Objective: To identify key predictors of clinical outcomes in burn survivors and clarify the role of mixed-depth burns and confounding by indication in observational rehabilitation research. Design: Retrospective cohort study using data from a burn r...

This study critically evaluates a recent machine learning method called the X-Learner, that aims to estimate treatment effects by predicting counterfactual quantities. It uses information from the treated group to predict counterfactuals for the cont...

With the aim to shorten the time for diagnosis and accelerate access to correct management, a non-invasive diagnostic test for endometriosis was developed and validated. The IVD test combines an ELISA test kit to quantify CA125 and BDNF concentration...

Background/Objectives: Temporomandibular disorders (TMDs) are a heterogeneous subset of orthodontic conditions with persistent diagnostic and reporting variability. This review compared transparency, reporting quality, and spin prevalence in TMD/TMJ...

Background: Causality has recently been suggested to associate early childhood caries with psychomotor deficiency in preschoolers, where their causal interactions via other risk determinants remain unclear. Methods: To analyze such causality, we rand...

Numerous variables can affect the assessment of language dominance using presurgical functional magnetic resonance (fMRI) in patients with brain tumors. This work organizes the variables into confounding and modulating factors. Confounding factors gi...

Electromagnetic (EM) medical technologies are rapidly expanding worldwide for both diagnostics and therapeutics. As these technologies are low-cost and minimally invasive, they have been the focus of significant research efforts in recent years. Such...

The relationships between selected upper airway-related symptoms (speech disturbances, voice disorders, cough, and breathing abnormalities) and mental illness and sleep disorders have been previously demonstrated. However, these relationships have no...

Measures of narcissism often overlap with global self-esteem, risking that observed associations with outcomes may reflect associations of self-regard rather than actual narcissistic dispositions. The present study examined whether common narcissism...

Background: Chimeric antigen receptor T-cell (CAR-T) therapies have been approved by the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) for the treatment of diffuse large B-cell lymphoma (DLBCL), primarily based on si...

Cough-based diagnosis for respiratory diseases (RDs) using artificial intelligence (AI) has attracted considerable attention, yet many existing studies overlook confounding variables in their predictive models. These variables can distort the relatio...

Introduction: The relation between physical well-being and chronic pain is complex and involves several subjective and objective covariates. We aimed to assess the role of mediator, confounder, or interactor played by covariates, including sleep qual...

The efficacy of bio-monitoring programs could be improved through addition of sensi- tive biomarkers. [...]

In observational causal inference studies, unmeasured confounding remains a critical threat to the validity of effect estimates. While proximal causal inference (PCI) has emerged as a powerful framework for mitigating such bias through proxy variable...

This study examines variability across the age span in cognitive performance in a cross-sectional, population-based, adult lifespan cohort from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) study (n = 2680). A key question we highlight i...

Despite considerable morbidity and mortality, numerous cases of endocrine hypertension (EHT) forms, including primary aldosteronism (PA), pheochromocytoma and functional paraganglioma (PPGL), and Cushing’s syndrome (CS), remain undetected. We a...

Supplement users (SU) make healthy lifestyle choices; on the other hand, SU report more medical conditions. We hypothesised that cod liver oil (CLO) consumers are similar to non-supplement users, since CLO use might originate from historical motives,...

When performing fractional factorial experiments in a completely random order is impractical, fractional factorial split-plot designs are suitable options as an alternative. It is well recognized that the more there are lower order effects of interes...

Background/Objectives: Understanding the relationship between dietary patterns, nutrient intake, and chronic disease risk is critical for public health strategies. However, confounding from lifestyle and individual factors complicates the assessment...

Demographic and clinical factors influence the metabolome. The discovery and validation of disease biomarkers are often challenged by potential confounding effects from such factors. To address this challenge, we investigated the magnitude of the cor...

Missing data remain a challenge for researchers and decision-makers due to their impact on analytical accuracy and uncertainty estimation. Many studies on missing data are based on randomness, but randomness itself is problematic. This makes it diffi...

(1) Background: Few studies have examined risk factors of frailty during early life and mid-adulthood, which may be critical to prevent frailty and/or postpone it. The aim was to identify early life and adulthood risk factors associated with frailty....

Background: Clinical guidelines recommend beta-blockers, angiotensin-converting enzyme inhibitors/angiotensin-receptor blockers, and statins for the secondary prevention of acute myocardial infarction (AMI). It is not clear whether variation in real-...

Biomarkers are becoming increasingly important for streamlining drug discovery and development. In addition, biomarkers are widely expected to be used as a tool for disease diagnosis, personalized medication, and surrogate endpoints in clinical resea...

Background: Alcohol and tobacco strongly increases the risk of cancers of the tongue, mouth, pharynx, larynx, and oesophagus, and are also established risk factors for cancer of the liver, colon, and rectum. It is well documented that these habits ar...

Background: The carriage of resistant bacteria and prior antimicrobial treatment are related, but in an individual, this diminishes over time. To better manage antimicrobial resistance risks, it is crucial that we better untangle any lasting impact o...

Typical statistical analysis of epidemiologic data captures uncertainty due to random sampling variation, but ignores more systematic sources of variation such as selection bias, measurement error, and unobserved confounding. Such sources are often o...

Monitoring soil moisture (SM) using permanently installed gamma radiation (GR) detectors is a promising non-invasive method based on the inverse relationship between SM and soil-emitted GR. In a previous study, we successfully estimated SM from envir...

Bounding causal effects under unmeasured confounding is particularly challenging when the outcome variable is ordinal. When the goal is to assess whether an intervention leads to a better outcome, ordinal causal effects offer a more appropriate analy...

Thanks to technological advances leading to near-continuous time observations, emerging multivariate point process data offer new opportunities for causal discovery. However, a key obstacle in achieving this goal is that many relevant processes may n...

The plasticity of responses to drugs is an ever-present confounding factor for all aspects of pharmacology, influencing drug discovery and development, clinical use and the expectations of the patient. As an introduction to this Special Issue of the...

Modelling causal relationships has become popular across various disciplines. Most common frameworks for causality are the Pearlian causal directed acyclic graphs (DAGs) and the Neyman-Rubin potential outcome framework. In this paper, we propose an i...

Estimating the effects of an intervention from high-dimensional observational data is a challenging problem due to the existence of confounding. The task is often further complicated in healthcare applications where a set of observations may be entir...

Methodologies employed in the production of systematic reviews used to inform policy must be robust. In formulating the recent World Health Organisation (WHO) Environmental Noise Guidelines for the European Region, seven systematic reviews of evidenc...

The association between air pollution and suicide has recently been under examination, and the findings continue to be contradictory. In order to contribute evidence to this still unresolved question, the objective of the present study was to evaluat...