2 citations · 2 across the 10 of their papers we have counts for
6 papers · 1 filter
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…
ProtoEHR: Hierarchical Prototype Learning for EHR-based Healthcare Predictions
Zi Cai, Yu Liu, Zhiyao Luo +1
Digital healthcare systems have enabled the collection of mass healthcare data in electronic healthcare records (EHRs), allowing artificial intelligence solutions for various healt…
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…
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…
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…