338 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- The University of Texas MD Anderson Cancer CenterUS17 papers
- The University of Texas Health Science CenterUS15 papers
- Yale UniversityUS13 papers
- Rice UniversityUS12 papers
- Fudan UniversityCN7 papers
- Harvard UniversityUS7 papers
- Mayo Clinic in FloridaUS7 papers
- National Institutes of HealthUS6 papers
- University of PennsylvaniaUS6 papers
- Texas A&M UniversityUS5 papers
- Baylor College of MedicineUS4 papers
- Cornell UniversityUS4 papers
15 papers · 1 filter
LLM-IE: A Python Package for Generative Information Extraction with Large Language Models
Enshuo Hsu, Kirk Roberts
Objectives: Despite the recent adoption of large language models (LLMs) for biomedical information extraction, challenges in prompt engineering and algorithms persist, with no dedi…
Explainable Diagnosis Prediction through Neuro-Symbolic Integration
Qiuhao Lu, Rui Li, Elham Sagheb +5
Diagnosis prediction is a critical task in healthcare, where timely and accurate identification of medical conditions can significantly impact patient outcomes. Traditional machine…
A Generative Framework for Predictive Modeling of Multiple Chronic Conditions Using Graph Variational Autoencoder and Bandit-Optimized Graph Neural Network
Julian Carvajal Rico, Adel Alaeddini, Syed Hasib Akhter Faruqui +2
Predicting the emergence of multiple chronic conditions (MCC) is crucial for early intervention and personalized healthcare, as MCC significantly impacts patient outcomes and healt…
FERI: A Multitask-based Fairness Achieving Algorithm with Applications to Fair Organ Transplantation
Can Li, Dejian Lai, Xiaoqian Jiang +1
Liver transplantation often faces fairness challenges across subgroups defined by sensitive attributes such as age group, gender, and race/ethnicity. Machine learning models for ou…
Self-explainable Graph Neural Network for Alzheimer's Disease And Related Dementias Risk Prediction
Xinyue Hu, Zenan Sun, Yi Nian +6
Background: Alzheimer's disease and related dementias (ADRD) ranks as the sixth leading cause of death in the US, underlining the importance of accurate ADRD risk prediction. While…
Split Learning for Distributed Collaborative Training of Deep Learning Models in Health Informatics
Zhuohang Li, Chao Yan, Xinmeng Zhang +4
Deep learning continues to rapidly evolve and is now demonstrating remarkable potential for numerous medical prediction tasks. However, realizing deep learning models that generali…
A Transformer-Based Deep Learning Approach for Fairly Predicting Post-Liver Transplant Risk Factors
Can Li, Xiaoqian Jiang, Kai Zhang
Liver transplantation is a life-saving procedure for patients with end-stage liver disease. There are two main challenges in liver transplant: finding the best matching patient for…
Multi-Task Learning for Post-transplant Cause of Death Analysis: A Case Study on Liver Transplant
Sirui Ding, Qiaoyu Tan, Chia-yuan Chang +5
Organ transplant is the essential treatment method for some end-stage diseases, such as liver failure. Analyzing the post-transplant cause of death (CoD) after organ transplant pro…
Towards Fair Patient-Trial Matching via Patient-Criterion Level Fairness Constraint
Chia-Yuan Chang, Jiayi Yuan, Sirui Ding +5
Clinical trials are indispensable in developing new treatments, but they face obstacles in patient recruitment and retention, hindering the enrollment of necessary participants. To…
Scalable Causal Structure Learning: Scoping Review of Traditional and Deep Learning Algorithms and New Opportunities in Biomedicine
Pulakesh Upadhyaya, Kai Zhang, Can Li +2
Causal structure learning refers to a process of identifying causal structures from observational data, and it can have multiple applications in biomedicine and health care. This p…
Deep Representation Learning of Patient Data from Electronic Health Records (EHR): A Systematic Review
Yuqi Si, Jingcheng Du, Zhao Li +5
Patient representation learning refers to learning a dense mathematical representation of a patient that encodes meaningful information from Electronic Health Records (EHRs). This…
Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis
Jing Ma, Qiuchen Zhang, Jian Lou +3
Tensor factorization has been demonstrated as an efficient approach for computational phenotyping, where massive electronic health records (EHRs) are converted to concise and meani…
A Robust Deep Learning Approach for Automatic Classification of Seizures Against Non-seizures
X. Yao, X. Li, Q. Ye +3
Identifying epileptic seizures through analysis of the electroencephalography (EEG) signal becomes a standard method for the diagnosis of epilepsy. Manual seizure identification on…
Early Prediction of Acute Kidney Injury in Critical Care Setting Using Clinical Notes
Yikuan Li, Liang Yao, Chengsheng Mao +3
Acute kidney injury (AKI) in critically ill patients is associated with significant morbidity and mortality. Development of novel methods to identify patients with AKI earlier will…
A Robust AUC Maximization Framework with Simultaneous Outlier Detection and Feature Selection for Positive-Unlabeled Classification
Ke Ren, Haichuan Yang, Yu Zhao +4
The positive-unlabeled (PU) classification is a common scenario in real-world applications such as healthcare, text classification, and bioinformatics, in which we only observe a f…