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…
From Token to Token Pair: Efficient Prompt Compression for Large Language Models in Clinical Prediction
Mingcheng Zhu, Zhiyao Luo, Yu Liu +1
By processing electronic health records (EHRs) as natural language sequences, large language models (LLMs) have shown potential in clinical prediction tasks such as mortality predi…
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…
Bridging Data Gaps of Rare Conditions in ICU: A Multi-Disease Adaptation Approach for Clinical Prediction
Mingcheng Zhu, Yu Liu, Zhiyao Luo +1
Artificial Intelligence has revolutionised critical care for common conditions. Yet, rare conditions in the intensive care unit (ICU), including recognised rare diseases and low-pr…
SegX: Improving Interpretability of Clinical Image Diagnosis with Segmentation-based Enhancement
Yuhao Zhang, Mingcheng Zhu, Zhiyao Luo
Deep learning-based medical image analysis faces a significant barrier due to the lack of interpretability. Conventional explainable AI (XAI) techniques, such as Grad-CAM and SHAP,…
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…