Air pollution caused by suspended particulate matter (PM) remains one of the key environmental challenges in Poland, particularly in the context of public health and spatial planning. This study presents a spatio-temporal analysis based on data from ...
CONTEXT: The extensive conformational space of flexible molecules poses a significant challenge for predicting chemical reactivity through quantum chemical methods. For curcumin, whose keto-enol tautomerization is crucial to its biological activity a...
BACKGROUND: We aimed to determine whether unsupervised machine learning was able to discover latent and possibly clinically-relevant clusters, hidden in dynamic electrical impedance tomography (EIT) images within a population of mechanically ventilat...
Journal of chemical information and modeling
Dec 31, 2025
Machine-learned interatomic models represent a significant advancement in simulation methods, extending the predictive ability of first-principles methods to previously inaccessible length and time scales. However, the data-driven nature of these mod...
Tracing the geographical origin of rice is of great significance in protecting the rights and interests of consumers and legitimate producers, as well as ensuring food safety. Here, we propose the combination of machine learning (ML) and clustering-t...
Rome IV disorders of gut-brain interaction (DGBI) subtypes are known to be unstable and demonstrate high rates of non-treatment response, likely indicating patient heterogeneity. Cluster analysis, a type of unsupervised machine learning, can identify...
Biomedical physics & engineering express
Dec 10, 2025
This study presents a fully unsupervised and label-independent radiomic pipeline designed to group different types of ischemic stroke lesions using multimodal Magnetic Resonance Imaging (MRI) . The aim is to address lesion heterogeneity and the absen...
UNLABELLED: Single-cell RNA sequencing (scRNA-seq) technology enables researchers to explore heterogeneity of diverse cell types within complex tissues at the single-cell resolution. Cell annotation, as a crucial step in scRNA-seq data analysis, prov...
A fundamental goal of genetics is to identify which and how genetic variants are associated with a trait, often using the regression results from genome-wide association (GWA) studies. Important methodological challenges account for inflation in GWA ...
The longitudinal course of epilepsy remains largely unpredictable. This study aimed to predict final outcome and classify dynamic longitudinal trajectories using artificial intelligence. A total of 2586 patients who first visited our epilepsy special...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.