World Health Organization (WHO) estimates 17.9 million deaths globally every year due to Cardiovascular Disease or CVD, which includes an array of disorders of the heart and blood vessels, that includes coronary heart disease, cerebrovascular disease...
The ongoing evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants highlights the importance of monitoring immune responses to guide vaccination strategies. Although neutralizing antibodies (NAbs) have garnered increasing ...
BACKGROUND: Lung cancer (LC) remains a leading cause of cancer-related mortality worldwide, primarily due to late-stage diagnosis and the absence of effective early detection methods.
BACKGROUND: Neoadjuvant chemotherapy (NAC) is gaining attention as a treatment for advanced colorectal cancer owing to its potential to improve surgical outcomes and prognosis. However, reliable biomarkers to predict the response to NAC are lacking. ...
Clinical reviews in allergy & immunology
Jul 8, 2025
Idiopathic inflammatory myopathies (IIM) are a group of autoimmune rheumatic diseases characterized by proximal muscle weakness and extra muscular manifestations. Since 1975, these IIM have been classified into different clinical phenotypes. Each cli...
Collection of systemic tissues from influenza A virus (IAV)-infected ferrets at a fixed timepoint post-inoculation represents a frequent component of risk assessment activities to assess the capacity of IAV to replicate systemically. However, few stu...
Genome sequencing from wastewater enables accurate and cost-effective identification of SARS-CoV-2 variants. However, existing computational pipelines have limitations in detecting emerging variants not yet characterized in humans. Here, we present a...
To improve the effectiveness of diabetes risk prediction, this study proposes a novel method based on focal active learning strategies combined with machine learning models. Existing machine learning models often suffer from poor performance on imbal...
PURPOSE: Machine learning is a powerful tool to develop algorithms for clinical diagnosis. However, standard machine learning algorithms are not perfectly suited for clinical data since the data are interconnected and may contain time series. As show...
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