Artificial Intelligence Medical Compendium

Recently, Video Question Answering (VideoQA) has garnered considerable research interest as a pivotal task within the realm of vision-language understanding. However, existing Video Question Answering datasets often lack sufficient entity and event i... read more 

Multi-view learning exploits the complementary nature of multiple modalities to enhance performance across diverse tasks. While deep learning has significantly advanced these fields by enabling sophisticated modeling of intra-view and cross-view inte... read more 

Interactive segmentation algorithms based on click points have attracted significant attention from researchers in recent years. However, most existing methods rely on sparse click maps as model inputs to segment specific target objects. These clicks... read more 

With rapid developments in artificial intelligence (AI), the discussion about and applications of generative AI have increased substantially. Generative AI has extensive and valuable applications in many industrial and medical fields and is a possibl... read more 

Conversational remembering is a core social process through which individual's co-construct personal and collective memories, maintains social bonds, and transmit cultural knowledge. This process is inherently multimodal, involving the coordination o... read more 

This article explores the application of big data and analytics in ambulatory medicine, population health, and inpatient medicine. The article highlights the benefits, challenges, and future directions of predictive analytics and artificial intellige... read more 

Personality changes surrounding transitions in life circumstances are often non-linear, presenting challenges for statistical analysis. This paper therefore reviews approaches to modelling non-linear personality change surrounding transitions, aiming... read more 

Video tasks play an important role in multimedia fields. In various video tasks, such as video camouflaged/salient object detection (VCOD/VSOD), motion and context information are two important aspects. Despite the fact that many existing works have ... read more 

OBJECTIVE: The aim of this study is to evaluate the prognostic performance of a nomogram integrating clinical parameters with deep learning radiomics (DLRN) features derived from ultrasound and multi-sequence magnetic resonance imaging (MRI) for pred... read more 

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