2 citations · 2 across the 6 of their papers we have counts for
8 papers
ECG Mirage: Revealing and Mitigating the Underutilisation of ECGs in Vision-Language Models for Clinical Prediction
Jinning Liang, Mingcheng Zhu, Tingting Zhu
Emergency department (ED) decision-making relies on heterogeneous clinical information, including patient history, vital signs, laboratory results, and electrocardiograms (ECGs). V…
The Taxonomies, Training, and Applications of Event Stream Modelling for Electronic Health Records
Mingcheng Zhu, Yu Liu, Zhiyao Luo +1
The widespread adoption of electronic health records (EHRs) enables the acquisition of heterogeneous clinical data, spanning lab tests, vital signs, medications, and procedures, wh…
Attention-Guided Fair AI Modeling for Skin Cancer Diagnosis
Mingcheng Zhu, Mingxuan Liu, Han Yuan +4
Artificial intelligence (AI) has shown remarkable promise in dermatology, offering accurate and non-invasive diagnosis of skin cancer. While extensive research has addressed skin t…
Cross-Representation Benchmarking in Time-Series Electronic Health Records for Clinical Outcome Prediction
Tianyi Chen, Mingcheng Zhu, Zhiyao Luo +1
Electronic Health Records (EHRs) enable deep learning for clinical predictions, but the optimal method for representing patient data remains unclear due to inconsistent evaluation…
Are Large Language Models Dynamic Treatment Planners? An In Silico Study from a Prior Knowledge Injection Angle
Zhiyao Luo, Tingting Zhu
Reinforcement learning (RL)-based dynamic treatment regimes (DTRs) hold promise for automating complex clinical decision-making, yet their practical deployment remains hindered by…
CogBench: A Large Language Model Benchmark for Multilingual Speech-Based Cognitive Impairment Assessment
Rui Feng, Zhiyao Luo, Wei Wang +5
Automatic assessment of cognitive impairment from spontaneous speech offers a promising, non-invasive avenue for early cognitive screening. However, current approaches often lack g…
Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination
Zhiyao Luo, Yangchen Pan, Peter Watkinson +1
In the rapidly changing healthcare landscape, the implementation of offline reinforcement learning (RL) in dynamic treatment regimes (DTRs) presents a mix of unprecedented opportun…
DTR-Bench: An in silico Environment and Benchmark Platform for Reinforcement Learning Based Dynamic Treatment Regime
Zhiyao Luo, Mingcheng Zhu, Fenglin Liu +4
Reinforcement learning (RL) has garnered increasing recognition for its potential to optimise dynamic treatment regimes (DTRs) in personalised medicine, particularly for drug dosag…