[HTML][HTML] Multimodal large language models in health care: applications, challenges, and future outlook

R AlSaad, A Abd-Alrazaq, S Boughorbel… - Journal of medical …, 2024 - jmir.org
In the complex and multidimensional field of medicine, multimodal data are prevalent and
crucial for informed clinical decisions. Multimodal data span a broad spectrum of data types …

Prototype-oriented hypergraph representation learning for anomaly detection in tabular data

S Li, Y Lu, S Jiu, H Huang, G Yang, J Yu - Information Processing & …, 2025 - Elsevier
Anomaly detection in tabular data holds significant importance across various industries
such as manufacturing, healthcare, and finance. However, existing methods are constrained …

AD-NEv: A Scalable Multilevel Neuroevolution Framework for Multivariate Anomaly Detection

M Pietroń, D Żurek, K Faber… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Anomaly detection tools and methods present a key capability in modern cyberphysical and
failure prediction systems. Despite the fast-paced development in deep learning …

IoT-FKGDL-SL: Anomaly Detection Framework Integrating Knowledge Distillation and a Swarm Learning for 5G IoT

L Tang, E Kou, W Zhang, Q Wu… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
Anomaly detection using multivariate time series (MTS) is critical for detecting abnormal
traffic and device failures in 5G Internet of Things (IoT) devices. The current anomaly …

Transformer-based Multivariate Time Series Anomaly Localization

C Shimillas, K Malialis, K Fokianos… - arXiv preprint arXiv …, 2025 - arxiv.org
With the growing complexity of Cyber-Physical Systems (CPS) and the integration of Internet
of Things (IoT), the use of sensors for online monitoring generates large volume of …