Latest AI and machine learning research in transplantation for healthcare professionals.
Recent advances in multimodal Reward Models (RMs) have shown significant promise in delivering reward signals to align vision models with human preferences. However, current RMs are generally restricted to providing direct responses or engaging in shallow reasoning processes with limited depth, often leading to inaccurate reward signals. We posit that incorporating explicit long chains of though...
Sepsis is a life threatening medical condition that occurs when the body has an extreme response to infection, leading to widespread inflammation, organ failure, and potentially death. Because sepsis can worsen rapidly, early detection is critical to saving lives. However, current diagnostic methods often identify sepsis only after significant damage has already occurred. Our project aims to add...
This paper presents the Maximal Compatibility Matching (MCM) framework, a novel assignment strategy for ride-hailing systems that explicitly incorpo...
Population pharmacokinetic (PopPK) modelling is a fundamental tool for understanding drug behaviour across diverse patient populations and enabling ...
We introduce brain2print, a web-based application that converts T1-weighted MRI scans into 3D printable models. By leveraging artificial intelligence ...
Large language models (LLMs) have achieved impressive performance across various domains. However, the substantial hardware resources required for t...
Mechanistic, multicellular, agent-based models are commonly used to investigate tissue, organ, and organism-scale biology at single-cell resolution....
Real-time (RT) dynamic MRI plays a vital role in capturing rapid physiological processes, offering unique insights into organ motion and function. A...
Driven by the advancements in generative AI, large machine learning models have revolutionized domains such as image processing, audio synthesis, an...
The recognition of endogenous peptides by HLA class I plays a crucial role in CD8+ T cell immune responses and human adaptive cell immune. Thus, the p...
Methylated RNA m6A immunoprecipitation sequencing (m6A-Seq) is a powerful technique for investigating transcriptome-wide m6A modification. However, mo...
To evaluate deep learning-based calcium segmentation and quantification on ECG-gated cardiac CT scans compared with manual evaluation. Automated calci...
In this paper, we propose a novel semantic-aided image communication framework for supporting the compatibility with practical separation-based codi...
Multimodal physiological signals, such as EEG, ECG, EOG, and EMG, are crucial for healthcare and brain-computer interfaces. While existing methods r...
The prevalence of Large Language Models (LLMs) is revolutionizing the process of writing code. General and code LLMs have shown impressive performan...
Blind and visually impaired (BVI) students face significant challenges in traditional educational settings. While screen readers and braille materia...
Accurate kinetic analysis of [$^{18}$F]FDG distribution in dynamic positron emission tomography (PET) requires anatomically constrained modelling of...
Age prediction from medical images or other health-related non-imaging data is an important approach to data-driven aging research, providing knowle...
Printed and flexible electronics (PFE) have emerged as the ubiquitous solution for application domains at the extreme edge, where the demands for lo...
Many soft robots struggle to produce dynamic motions with fast, large displacements. We develop a parallel 6 degree-of-freedom (DoF) Stewart-Gough m...