250 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Xiaoqian Jiang3 profiles5 · h 23
- Hua Xu3 profiles4 · h 7
- Jingcheng Du3 profiles4 · h 21
- Kirk Roberts3 profiles4 · h 36
- Rui Zhang3 profiles3 · h 77
- Yan Hu2 profiles3 · h 9
- Zhiyong Lu2 profiles3 · h 18
- Cui Tao2 profiles2 · h 30
- Fang Li2 profiles2 · h 12
- Jimin Huang2 profiles2 · h 19
- Kalpana Raja2 profiles2 · h 15
- Qingyu Chen2 profiles2 · h 32
- The University of Texas Health Science Center at HoustonUS15 papers
- Yale UniversityUS4 papers
- The University of Texas MD Anderson Cancer CenterUS3 papers
- National Institutes of HealthUS2 papers
- United States National Library of MedicineUS2 papers
- University of Maryland, BaltimoreUS2 papers
- Baylor College of MedicineUS1 paper
- Boston Children's HospitalUS1 paper
- Cornell UniversityUS1 paper
- Foundation for the National Institutes of HealthUS1 paper
- Harvard UniversityUS1 paper
- Houston MethodistUS1 paper
17 papers
Memorization in Large Language Models in Medicine: Prevalence, Characteristics, and Implications
Anran Li, Lingfei Qian, Mengmeng Du +18
Large Language Models (LLMs) have demonstrated significant potential in medicine, with many studies adapting them through continued pre-training or fine-tuning on medical data to e…
A Comparative Study of Recent Large Language Models on Generating Hospital Discharge Summaries for Lung Cancer Patients
Yiming Li, Fang Li, Kirk Roberts +3
Generating discharge summaries is a crucial yet time-consuming task in clinical practice, essential for conveying pertinent patient information and facilitating continuity of care.…
Suicide Phenotyping from Clinical Notes in Safety-Net Psychiatric Hospital Using Multi-Label Classification with Pre-Trained Language Models
Zehan Li, Yan Hu, Scott Lane +7
Accurate identification and categorization of suicidal events can yield better suicide precautions, reducing operational burden, and improving care quality in high-acuity psychiatr…
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…
Leveraging Large Language Models for Knowledge-free Weak Supervision in Clinical Natural Language Processing
Enshuo Hsu, Kirk Roberts
The performance of deep learning-based natural language processing systems is based on large amounts of labeled training data which, in the clinical domain, are not easily availabl…
GENEVIC: GENetic data Exploration and Visualization via Intelligent interactive Console
Anindita Nath, Savannah Mwesigwa, Yulin Dai +2
Summary: The vast generation of genetic data poses a significant challenge in efficiently uncovering valuable knowledge. Introducing GENEVIC, an AI-driven chat framework that tackl…
Advancing bioinformatics with large language models: components, applications and perspectives
Jiajia Liu, Mengyuan Yang, Yankai Yu +4
Large language models (LLMs) are a class of artificial intelligence models based on deep learning, which have great performance in various tasks, especially in natural language pro…
Evaluating the effects of high-throughput structural neuroimaging predictors on whole-brain functional connectome outcomes via network-based vector-on-matrix regression
Tong Lu, Yuan Zhang, Vince Lyzinski +4
The joint analysis of multimodal neuroimaging data is critical in the field of brain research because it reveals complex interactive relationships between neurobiological structure…
Benchmarking large language models for biomedical natural language processing applications and recommendations
Qingyu Chen, Yan Hu, Xueqing Peng +18
The rapid growth of biomedical literature poses challenges for manual knowledge curation and synthesis. Biomedical Natural Language Processing (BioNLP) automates the process. While…
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…
Deep Learning Provides Rapid Screen for Breast Cancer Metastasis with Sentinel Lymph Nodes
Kareem Allam, Xiaohong Iris Wang, Songlin Zhang +6
Deep learning has been shown to be useful to detect breast cancer metastases by analyzing whole slide images of sentinel lymph nodes. However, it requires extensive scanning and an…
Mining On Alzheimer's Diseases Related Knowledge Graph to Identity Potential AD-related Semantic Triples for Drug Repurposing
Yi Nian, Xinyue Hu, Rui Zhang +5
To date, there are no effective treatments for most neurodegenerative diseases. Knowledge graphs can provide comprehensive and semantic representation for heterogeneous data, and h…
Generalized and Transferable Patient Language Representation for Phenotyping with Limited Data
Yuqi Si, Elmer V Bernstam, Kirk Roberts
The paradigm of representation learning through transfer learning has the potential to greatly enhance clinical natural language processing. In this work, we propose a multi-task 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…
Drug repurposing for COVID-19 using graph neural network and harmonizing multiple evidence
Kanglin Hsieh, Yinyin Wang, Luyao Chen +5
Amid the pandemic of 2019 novel coronavirus disease (COVID-19) infected by SARS-CoV-2, a vast amount of drug research for prevention and treatment has been quickly conducted, but t…
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…
Replays of spatial memories suppress topological fluctuations in cognitive map
Andrey Babichev, Dmitriy Morozov, Yuri Dabaghian
The spiking activity of the hippocampal place cells plays a key role in producing and sustaining an internalized representation of the ambient space---a cognitive map. These cells…