With the growth of data and intelligent technologies, the healthcare sector opened numerous
technology that enabled services for patients, clinicians, and researchers. One major hurdle …

The field of oncology has witnessed an extraordinary surge in the application of big data and
artificial intelligence (AI). AI development has made multiscale and multimodal data fusion …

With the increasing availability of multimodal educational data, there is a growing need to
effectively integrate and exploit multiple data sources to enhance student engagement …

How can we better extract entities and relations from text? Using multimodal extraction with
images and text obtains more signals for entities and relations, and aligns them through …

Patient-Centric Knowledge Graphs (PCKGs) represent an important shift in healthcare that
focuses on individualized patient care by map** the patient's health information …

Video action segmentation have been widely applied in many fields. Most previous studies
employed video-based vision models for this purpose. However, they often rely on a large …

Objectives This study focuses on refining temporal relation extraction within medical
documents by introducing an innovative bimodal architecture. The overarching goal is to …

The rapid advancement in healthcare data collection technologies and the importance of
using multimodal data for accurate diagnosis leads to a surge in multimodal data …

Multimodal data pervades various domains, including healthcare, social media, and
transportation, where multimodal graphs play a pivotal role. Machine learning on multimodal …

Radiology reports serve as a fundamental component within electronic medical records.
Converting unstructured free-text reports into structured formats holds paramount …