79 citations · 140 across the 19 of their papers we have counts for
11 papers · 1 filter
GraphWalker: Patient Analogy Meets Information Gain for Clinical Reasoning with Large Language Models
Yue Fang, Weibin Liao, Yuxin Guo +8
Clinical reasoning over electronic health records (EHRs) is a fundamental yet challenging task in modern healthcare. While large language models (LLMs) offer a promising paradigm v…
ColaCare: Enhancing Electronic Health Record Modeling through Large Language Model-Driven Multi-Agent Collaboration
Zixiang Wang, Yinghao Zhu, Huiya Zhao +9
We introduce ColaCare, a framework that enhances Electronic Health Record (EHR) modeling through multi-agent collaboration driven by Large Language Models (LLMs). Our approach seam…
Predict and Interpret Health Risk using EHR through Typical Patients
Zhihao Yu, Chaohe Zhang, Yasha Wang +3
Predicting health risks from electronic health records (EHR) is a topic of recent interest. Deep learning models have achieved success by modeling temporal and feature interaction.…
Domain-invariant Clinical Representation Learning by Bridging Data Distribution Shift across EMR Datasets
Zhongji Zhang, Yuhang Wang, Yinghao Zhu +7
Emerging diseases present challenges in symptom recognition and timely clinical intervention due to limited available information. An effective prognostic model could assist physic…
Mortality Prediction with Adaptive Feature Importance Recalibration for Peritoneal Dialysis Patients: a deep-learning-based study on a real-world longitudinal follow-up dataset
Liantao Ma, Chaohe Zhang, Junyi Gao +8
Objective: Peritoneal Dialysis (PD) is one of the most widely used life-supporting therapies for patients with End-Stage Renal Disease (ESRD). Predicting mortality risk and identif…
A Comprehensive Benchmark for COVID-19 Predictive Modeling Using Electronic Health Records in Intensive Care
Junyi Gao, Yinghao Zhu, Wenqing Wang +4
The COVID-19 pandemic has posed a heavy burden to the healthcare system worldwide and caused huge social disruption and economic loss. Many deep learning models have been proposed…
MedFACT: Modeling Medical Feature Correlations in Patient Health Representation Learning via Feature Clustering
Xinyu Ma, Xu Chu, Yasha Wang +4
In healthcare prediction tasks, it is essential to exploit the correlations between medical features and learn better patient health representations. Existing methods try to estima…
CovidCare: Transferring Knowledge from Existing EMR to Emerging Epidemic for Interpretable Prognosis
Liantao Ma, Xinyu Ma, Junyi Gao +7
Due to the characteristics of COVID-19, the epidemic develops rapidly and overwhelms health service systems worldwide. Many patients suffer from systemic life-threatening problems…
StageNet: Stage-Aware Neural Networks for Health Risk Prediction
Junyi Gao, Cao Xiao, Yasha Wang +3
Deep learning has demonstrated success in health risk prediction especially for patients with chronic and progressing conditions. Most existing works focus on learning disease Netw…
ConCare: Personalized Clinical Feature Embedding via Capturing the Healthcare Context
Liantao Ma, Chaohe Zhang, Yasha Wang +6
Predicting the patient's clinical outcome from the historical electronic medical records (EMR) is a fundamental research problem in medical informatics. Most deep learning-based so…
AdaCare: Explainable Clinical Health Status Representation Learning via Scale-Adaptive Feature Extraction and Recalibration
Liantao Ma, Junyi Gao, Yasha Wang +6
Deep learning-based health status representation learning and clinical prediction have raised much research interest in recent years. Existing models have shown superior performanc…