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Incorporating polarization in computer vision tasks provides new solutions to high-level analytics, in particular when coupled with machine learning frameworks such as convolutional neural networks (CNN). A recent review...

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...

Detection of atypical response trajectories in biomedical longitudinal databases Many health care professionals and institutions manage longitudinal databases, involving follow-ups for different patients over time. Longi...

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...

The paper analyzes the existing non-invasive methods and tools for measuring and monitoring heart rate (HR), glucose saturation and human blood glucose level (BGL), shows ways of improving them to increase accuracy and e...

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...

Abstract Introduction Suicide is a serious public health problem that affects the whole world. This study describes development of the prototype for an mHealth application (app) intended to assist healthcare profession...

Precisely pinpointing the positions of emitters within the diffraction limit is crucial for quantitative analysis or molecular mechanism investigation in biomedical research but has remained challenging unless exploiting...