Recent advances in estimation techniques have underscored the growing importance of shrinkage estimation and balanced loss functions in the analysis of multivariate normal distributions. These ...
This study investigated the dynamics of human cortical network activity with functional magnetic resonance imaging during movie watching and studied the modulation of these dynamics by subcortical ...
Mathematicians are still trying to understand fundamental properties of the Fourier transform, one of their most ubiquitous ...
Abstract: The imagery speech (IS) is the speech that the human beings are thinking in their brain. A brain computer interface (BCI) system is employed to translate the speech thinking in the brain to ...
Abstract: Graph learning-based multi-modal integration and classification is one of the most challenging tasks for disease prediction. To effectively offset the negative impact among modalities in the ...
Detecting anomalies in multivariate time series (MTS) is essential for maintaining system safety in industrial environments. Due to the challenges associated with acquiring labeled data, unsupervised ...
Purpose: This study aimed to develop a predictive model for assessing the efficacy of neoadjuvant chemotherapy (NAC) in patients with Human Epidermal Growth Factor Receptor 2 (HER2)-low breast cancer, ...
Context Aware RAG is a flexible library designed to seamlessly integrate into existing data processing workflows to build customized data ingestion and retrieval (RAG) pipelines. With Context Aware ...
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