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Abstract Background In biomedical research, subjects and biospecimens are commonly tracked using simple IDs or UUIDs, which guarantee uniqueness but convey no embedded semantic information. Contextual metadata (such as t...

Abstract Precise extraction of medical phenotypes and entities from electronic health record (EHR) text is vital for numerous clinical research tasks, including cohort classification, tracking temporal patterns in diseas...

Abstract Using biomedical foundation models (FMs) for inference on small cohorts, represents a promising and practical route to advance drug response biomarker discovery and target identification. Here, we demonstrate th...

Abstract Background Single-cell RNA sequencing (scRNA-seq) is considered a revolution in gene expression studies and offers significant benefits across various fields of biomedical or clinical applications. However, a hi...

Abstract Access to large, diverse biomedical datasets is critical for advancing medical research, yet privacy regulations severely restrict data sharing. We present an end-to-end framework for privacy-preserving health d...

Abstract Background There has been a recent push for biomedical research to incorporate more demographically, ethnically, and medically diverse cohorts – individuals whom the NIH designates as “underrepresented in bi...

Abstract Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems have significantly advanced data modelling capabilities and improved opportunities for extracting knowledge from vast and heterogeneo...

Small sample sizes in preclinical research limit the extraction of reliable knowledge and hinder translational progress. We propose genESOM, a generative artificial intelligence method based on emergent self‑organizing...

BackgroundYupingfeng Powder (YPF), a classical Chinese herbal formula composed of Astragalus membranaceus, Atractylodes macrocephala, and Saposhnikovia divaricata, has demonstrated potential efficacy in the treatment of ...

Abstract Detecting epileptic seizures from electroencephalogram (EEG) signals presents a significant challenge due to the nonlinear and non-stationary nature of brain activity. In this study, we propose a hybrid classifi...

Electroencephalography (EEG) is a crucial technique for interpreting neurocognitive functions and the underlying neural information. Despite its advantages, such as high portability, cost-effectiveness and exceptional te...

ABSTRACT Background and Aims Late diagnosis of chronic hepatitis B and C, often identified by the presence of advanced disease such as hepatocellular carcinoma or decompensated cirrhosis at the time of initial hepatitis ...

Abstract Quantum Machine Learning (QML) is emerging as a promising technology for tackling complex computational challenges, although its practical implementation faces significant obstacles owed to the inherent noise in...

Abstract Finding interesting phenomena is the core of scientific discovery, but the notion of interestingness is vaguely defined and heavily reliant on manual judgment. We present InterFeat, an integrative pipeline for a...

Abstract Intertidal macrobenthos are vital bioindicators of coastal ecosystem health due to their ecological roles, limited mobility, and sensitivity to environmental disturbances. However, traditional field‐based moni...

Abstract This research employs hybrid machine learning techniques to optimize the mechanical properties of 3D-printed polylactic acid (PLA) lattice structures. By integrating random forest (RF) and XGBoost (XGB) algorith...

Abstract Parkinson’s Disease (PD) is a progressive neurodegenerative disorder that causes motor and cognitive impairments, affecting approximately 1% of individuals over 60 years of age. Speech impairments are among th...

Abstract Background Social participation, a principle that has guided health reform processes globally, presents diverse barriers according to the political and social context, obstructing its effective exercise. This st...

Abstract Background Reliable identification of protein‑protein interactions (PPIs) is crucial for deciphering cellular functional networks. Current research models still face limitations in aligning heterogeneous featu...

ObjectiveTo systematically evaluate the effects of exercise therapies such as aerobic exercise (CAE), Tai Chi (TC), Baduanjin (BDJ), resistance training (RE), Wuqinxi (WQX), yoga (YG), and rehabilitation training (RT) on...

Background Technology-based gait rehabilitation after stroke is expanding, however the extent to which interventions embody person-centred care remains unclear. Aims The objective of this review is to explore the extent ...

Abstract Background As the global incidence of pediatric Inflammatory Bowel Disease (IBD) rises, so does the complexity of its psychosocial burden. While biomedical protocols for clinical management are robust, the subje...

Abstract Background The National Institutes of Health (NIH) Sex as a Biological Variable (SABV) policy aims to improve the rigor and reproducibility of biomedical research by encouraging sex-inclusive study designs and s...

Abstract This model is highly helpful in thermal management and complex energy systems, particularly where precise control over heat and mass transfer is required. Solarized nanofluids can be used to improve heat absorpt...