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
4 papers · 1 filter
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…