Latest AI and machine learning research in medical ethics / professional responsibility for healthcare professionals.
Human decision-making in cognitive tasks and daily life exhibits considerable variability, shaped by factors such as task difficulty, individual preferences, and personal experiences. Understanding this variability across individuals is essential for uncovering the perceptual and decision-making mechanisms that humans rely on when faced with uncertainty and ambiguity. We present a computational ...
Quantitative Systems Pharmacology (QSP) promises to accelerate drug development, enable personalized medicine, and improve the predictability of clinical outcomes. Realizing its full potential depends on effectively managing the complexity of the underlying mathematical models and biological systems. Here, we present and validate a novel QSP workflow grounded in the principles of sloppy modeling...
There is an urgent need to develop tools to enable older adults to live healthy, independent lives for as long as possible. To address this need, the ...
Manual annotation of volumetric medical images, such as magnetic resonance imaging (MRI) and computed tomography (CT), is a labor-intensive and time...
The widespread adoption of Artificial Intelligence (AI) has been driven by significant advances in intelligent system research. However, this progre...
Generative artificial intelligence (AI) algorithms for both text-to-text and text-to-image applications have seen rapid and widespread adoption in the...
With the widespread application of large language models (LLMs), the issue of generating non-existing facts, known as hallucination, has garnered in...
Understanding actions within surgical workflows is essential for evaluating post-operative outcomes. However, capturing long sequences of actions pe...
Time series classification (TSC) is a critical task with applications in various domains, including healthcare, finance, and industrial monitoring. ...
The de-identification of private information in medical data is a crucial process to mitigate the risk of confidentiality breaches, particularly whe...
This paper introduces the Cable Robot Simulation and Control (CaRoSaC) Framework, which integrates a simulation environment with a model-free reinfo...
Human instance matting aims to estimate an alpha matte for each human instance in an image, which is challenging as it easily fails in complex cases...
In recent years, research has mainly focused on the general NER task. There still have some challenges with nested NER task in the specific domains....
Despite the growing research on users' perceptions of health AI, adolescents' perspectives remain underexplored. This study explores adolescents' pe...
Reliable tumor segmentation in thoracic computed tomography (CT) remains challenging due to boundary ambiguity, class imbalance, and anatomical vari...
With the growing density of wireless networks and demand for multi-hop transmissions, precise delay Quality of Service (QoS) analysis has become a c...
Electrical impedance tomography (EIT) is a non-invasive imaging method with diverse applications, including medical imaging and non-destructive test...
Efficient and accurate evaluation of containment queries for regions bound by trimmed NURBS surfaces is important in many graphics and engineering a...
Wheat accounts for approximately 20% of the world's caloric intake, making it a vital component of global food security. Given this importance, mapp...
In this paper we develop automatic shape differentiation techniques for unfitted discretisations and link these to recent advances in shape calculus...