Weizi Li

P044 Multi-centre service evaluation of the rheumatology advice line with suggestions for developing a national solution using artificial intelligence

Sarah Ryan, Julie Begum, Alexandra Eden, Patricia Cornell et autres

Abstract Background/Aims Advice lines are essential for the delivery of rheumatology services. The lowering of disease thresholds for biologic and advanced therapies, together with the ageing population, means a greater complexity of patient-care and increase in the number of adviceline queries. However, …

gb, us (code pays fourni par la source)

Explainable machine learning for predicting disease flares in axial spondyloarthritis: A real-world electronic health record-based pilot study

Antoni Chan, Pradip Moon, Weizi Li, Eghosa Bazuaye

Objective: Flares of axial spondyloarthritis (axSpA) are common yet unpredictable. We aimed to develop and internally validate a machine learning (ML) model to forecast flares 3, 6, 9 and 12 months ahead using routinely collected electronic health record (EHR) data. Methods: We …

gb (code pays fourni par la source)

HSD68 Lean Assessment Process Methodology for RMD-Health: Evaluating Clinical Need Usefulness Adoption Barriers and Early Economic Value of AI in NHS Rheumatology Referrals

Weizi Li, James D. Rose, Mamta Bajre

gb (code pays fourni par la source)

Explainable machine learning-based prediction of psoriatic arthritis flares using heterogenous real-world data for personalised patient care

Pradip Moon, Weizi Li, Antoni T.Y. Chan, Bing Wang et autres

Psoriatic arthritis (PsA) is a chronic inflammatory disease characterised by unpredictable flare-ups that are difficult to forecast, particularly in patients without an acute phase response. In this paper, we propose and apply an explainable, multimodal machine learning framework that jointly leverages structured …

gb (code pays fourni par la source)

MIAT: Maneuver-Intention-Aware Transformer for Spatio-Temporal Trajectory Prediction

Chandra Raskoti, Iftekharul Islam, Xuan Wang, Weizi Li

Accurate vehicle trajectory prediction is critical for safe and efficient autonomous driving, especially in mixed traffic environments when both human-driven and autonomous vehicles co-exist. However, uncertainties introduced by inherent driving behaviors—such as acceleration, deceleration, and left and right maneuvers—pose significant challenges for …

us (code pays fourni par la source)

Human-Robot Co-Transportation using Disturbance-Aware MPC with Pose Optimization

Al Jaber Mahmud, Amir Hossain Raj, Duc Minh Nguyen, Weizi Li et autres

This paper proposes a new control algorithm for human-robot co-transportation using a robot manipulator equipped with a mobile base and a robotic arm. We integrate the regular Model Predictive Control (MPC) with a novel pose optimization mechanism to more efficiently mitigate disturbances …

us (code pays fourni par la source)

Optimising Multimedia Learning: Effects of Pedagogical Agents' Appearance and Voice

Mengshi Xiao, Weizi Li, Lei Han, Shasha Zheng

ABSTRACT Background In multimedia learning environments, pedagogical agents have emerged as an innovative tool to enhance digital instruction, yet optimising their design for maximal learning effectiveness remains underexplored. Objectives This study aimed to investigate how specific design elements of pedagogical agents, namely …

cn (code pays fourni par la source)

Origin-Destination Pattern Effects on Large-Scale Mixed Traffic Control via Multi-Agent Reinforcement Learning

Songyang Liu, Shuai Li, Weizi Li

Traffic congestion remains a major challenge for modern urban transportation, diminishing both efficiency and quality of life. While autonomous driving technologies and reinforcement learning (RL) have shown promise for improving traffic control, most prior work has focused on small-scale networks or isolated …

Corrigendum to “Multi-stage multimodal fusion network with language models and uncertainty evaluation for early risk stratification in rheumatic and musculoskeletal diseases” [Information Fusion, Volume 120 (2025) 103068]

Bing Wang, Weizi Li, Anthony Bradlow, A. Watt et autres

gb (code pays fourni par la source)

Personalized uncertainty quantification in artificial intelligence

Tapabrata Chakraborti, Christopher R. S. Banerji, Ariane Marandon, Vicky Hellon et autres

gb (code pays fourni par la source)

P187 Prediction of flares in psoriatic arthritis using a machine learning approach to improve patient care

Pradip Moon, Weizi Li, Eghosa Bazuaye, Antoni T.Y. Chan

Abstract Background/Aims Treatment of psoriatic arthritis (PsA) involves the management of flares which can be unpredictable. Patients with flares may have long-term joint damage if it is recurrent or not promptly treated. Artificial intelligence (AI) and natural language processing (NLP) methods provide …

gb (code pays fourni par la source)

Mutual Adaptation in Human-Robot Co-Transportation with Human Preference Uncertainty

Al Jaber Mahmud, Weizi Li, Xuan Wang

Mutual adaptation can enhance overall task performance in human-robot co-transportation by integrating both the robot's and the human's understanding of the environment. While human modeling helps capture humans' subjective preferences, two challenges persist: (i) the uncertainty of human preference parameters and (ii) …