Latest AI and machine learning research in surveys for healthcare professionals.
Multimodal coding and editing systems must map a visible or semantic referent to the exact executabl...
Conventional federated learning (FL) relies on parameter averaging, which forces clients to be doubl...
Background: Systematic reviews of clinical prediction models increasingly include studies using arti...
Accurate uncertainty estimation is essential for machine learning systems de- ployed in high-stakes ...
While face recognition systems are widely deployed, ensuring their demographic reliability and robus...
Long-tailed distributions are prevalent in real-world semi-supervised learning (SSL), where pseudo-l...
We propose a societal bias evaluation method for large vision-language models (LVLMs) in the era of ...
Text-to-image models learn associations between concepts - in the case of this paper, people's profe...
Molecules generated by deep learning models are often difficult to synthesize. Their synthetic acces...
Neonatal mortality risk prediction from bedside monitoring data remains challenging due to extreme c...
Generative vision-language models (VLMs) are increasingly used in human-centered settings, yet they ...
Control variables are widely used in statistical modelling to account for omitted variable bias of k...
Three-dimensional probabilistic inversion of time-domain airborne electromagnetic (AEM) data is limi...
Spatial multi-omics technologies jointly profile gene expression, surface proteins, and histology at...
Background: Large language models (LLMs) have shown increasing capability in medical knowledge tasks...
Abstract EEG foundation models (EEG-FMs) are evaluated almost entirely on disease-discrimination acc...
Spatial multi-omics technologies jointly profile gene expression, surface proteins, and histology at...
Background. Phthalates are hypothesised to act as metabolic disruptors, and machine learning applied...
Promptable segmentation models provide a reusable interface, but direct transfer to automatic infrar...
Travel behavior research increasingly combines digital data collection with predictive modeling, yet...
Irregular time series forecasting is crucial in many domains, such as healthcare and meteorological ...