Latest AI and machine learning research in practice management for healthcare professionals.
Large language models (LLMs) hold significant potential for mental health support, capable of generating empathetic responses and simulating therapeutic conversations. However, existing LLM-based approaches often lack the clinical grounding necessary for real-world psychological counseling, particularly in explicit diagnostic reasoning aligned with standards like the DSM/ICD and incorporating di...
Efficient video coding is highly dependent on exploiting the temporal redundancy, which is usually achieved by extracting and leveraging the temporal context in the emerging conditional coding-based neural video codec (NVC). Although the latest NVC has achieved remarkable progress in improving the compression performance, the inherent temporal context propagation mechanism lacks the ability to s...
A key trend in Large Reasoning Models (e.g., OpenAI's o3) is the native agentic ability to use external tools such as web browsers for searching and...
The biological implausibility of backpropagation (BP) has motivated many alternative, brain-inspired algorithms that attempt to rely only on local i...
Palliative care is known to improve quality of life in advanced cancer. Natural language processing offers insights to how documentation around pallia...
Doctors and patients alike increasingly use Large Language Models (LLMs) to diagnose clinical cases. However, unlike domains such as math or coding,...
High computation costs and latency of large language models such as GPT-4 have limited their deployment in clinical settings. Small language models ...
Identifying the Underlying Cause of Death accurately is crucial for effective healthcare policy and planning. The World Health Organization recommends...
Background: The use of social robotics in elderly care is increasingly discussed as one way of meeting emerging care needs due to scarce resources. ...
We propose a mathematical framework to systematically explore the propagation properties of a class of continuous in time nonlinear neural network m...
OBJECTIVES: Administrative data are commonly used to inform chronic disease prevalence and support health informatic research. This study assessed the...
This paper introduces feature-based behavior coding (FBBC), an efficient method for exploratory analysis in behavioral research using pose estimation ...
Generative AI systems have revolutionized human interaction by enabling natural language-based coding and problem solving. However, the inherent amb...
Learned video coding (LVC) has recently achieved superior coding performance. In this paper, we model the rate-quality (R-Q) relationship for learne...
Real-time transmission of visual data over wireless networks remains highly challenging, even when leveraging advanced deep neural networks, particu...
Virtual studies of ICD behaviour are crucial for testing device functionality in a controlled environment prior to clinical application. Although pr...
The integration of Large Language Models (LLMs) like GPT-4 with Extended Reality (XR) technologies offers the potential to build truly immersive XR en...
Agentic systems built on large language models (LLMs) offer promising capabilities for automating complex workflows in healthcare AI. We introduce m...
The rapid development of AIGC foundation models has revolutionized the paradigm of image compression, which paves the way for the abandonment of mos...
In this paper, we propose a novel semantic-aided image communication framework for supporting the compatibility with practical separation-based codi...