Latest AI and machine learning research in clinical trials for healthcare professionals.
Despite biomarker-guided treatment strategies, clinical outcomes among patients with type 2 (T2)-high asthma remain heterogeneous, with some patients responding poorly to T2-targeted biologic therapies. We developed a contrastive machine learning method for patient stratification based on whole-blood DNA methylation (DNAm), applying it to pediatric asthma cohorts of Latino (discovery; n=1,016) and...
Current Czech national food-based dietary guidelines are outdated and do not reflect the most recent scientific evidence, nor considerations of sustainability and equity. Building on the Nordic Nutrition Recommendations 2023 (NNR), this project aims to develop updated, evidence-based food-based dietary guidelines (FBDGs) for the Czech Republic. To systematically update the evidence on associations...
Resource Constrained Situations (RCS) at Emergency Medical Dispatch centers where there are more patients requiring an ambulance than there are availa...
Machine learning (ML) algorithms are increasingly used to estimate propensity score with expectation of improving causal inference. However, the valid...
Recovery from aphasia after stroke is thought to depend on functional reorganization of language processing in surviving brain regions. Many studies h...
The global prevalence of overweight and obesity continues escalating, driven by environmental factors and lifestyle behaviors leading to cardiovascula...
Large language models (LLMs) show promise for improving clinical reasoning, but they also risk inducing automation bias, an over-reliance that can deg...
With a goal of unveiling mechanisms by which vaccines can provide protection against HIV-1 acquisition, several studies have explored correlates of ri...
Perceived trustworthiness of research may be influenced by factors beyond the risk of bias, including study-related characteristics, research context,...
Dysmenorrhea, or menstrual pain, is a prevalent issue among female university students that negatively influences their productivity, academic perform...
To develop privacy-enhancing statistical methods for estimation of binary disease risk model association parameters across multiple electronic health ...
Conversational agents based on large language models (LLMs) have shown moderate efficacy in reducing depressive and anxiety symptoms. However, most ex...
Cancer cachexia, a multifactorial metabolic syndrome characterized by severe muscle wasting and weight loss, contributes to poor outcomes across vario...
Information from electronic health records (EHRs) may be incorporated into computable phenotype algorithms in efforts to overcome inaccuracies of algo...
Prior research suggests that meditation may slow brain aging and reduce the risk of Alzheimer’s disease (AD). However, we lack research systematically...
Mental illness is often characterised by a maladaptive sense of self. The neurobiological basis of Self-Other distinction may provide targets for ther...
Large language models (LLMs) show promise on healthcare tasks, yet most evaluations emphasize multiple-choice accuracy rather than open-ended reasonin...
Music engages sensory, motor, cognitive, and emotional systems, making it a powerful model for studying experience-dependent neuroplasticity. Although...
Overall survival (OS) remains the gold standard for oncology drug approval, but measuring it requires long follow-up and is impractical in certain onc...
Predicting the likelihood of developing Alzheimer’s disease (AD) dementia in at-risk individuals is important for the design of and optimal recruitmen...