基本信息
views: 426
![](https://originalfileserver.aminer.cn/sys/aminer/icon/show-trajectory.png)
Bio
Dr. Li is a behavioral statistician with a joint appointment in the Department of Psychiatry & Behavioral Sciences and the Department of Epidemiology and Biostatistics. His expertise is in Bayesian Item Response Theory and Bayesian Multilevel Modeling. His current research focuses on Bayesian Nonparametric methods in psychology as well as Patient-Reported Outcomes data analysis using Machine Learning analytics, including Dirichlet Process Mixture Modeling (PMID: 31217637) on psychological symptom clusters for patients with advanced/terminal cancer near the end of life and Latent Dirichlet Allocation to score patients’ quality of life (PMID: 30798421). Clinicians are no longer restricted by conventional QOL surveys which rely on fixed (and often lengthy) surveys that routinely neglect each patient’s idiosyncratic goals and priorities. Patients’ goals can now be incorporated to enhance conventional data from fixed-length QOL measures. Dr. Li also works on making these revolutionary ideas accessible to behavioral scientists in his tutorials on Bayesian psychometric methods (PMID: 29424559, 22362655, 27193366).
Research Interests
Papers共 233 篇Author StatisticsCo-AuthorSimilar Experts
By YearBy Citation主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
Tony K W Hung,Nicholas P Verdini, Jaime L Gilliland, Susan Chimonas,Jennifer R Cracchiolo,Yuelin Li,David G Pfister,Erin F Gillespie
Sunny Nalavenkata,Oskar Bergengren, Zara McPartland, Daniela Shill, Khadra Dualeh,Kathleen Lynch,Nicholas Emard, Sené Martin,Mia Austria,Gabriel Ogbennaya, Jason Gonsky,Andrew Vickers,
JCO GLOBAL ONCOLOGYno. 9 (2023): e2300159-e2300159
The Journal of urology/The journal of urologyno. Supplement 5 (2022)
Cited0Views0Bibtex
0
0
arXiv (Cornell University) (2021)
Load More
Author Statistics
#Papers: 229
#Citation: 4196
H-Index: 26
G-Index: 59
Sociability: 7
Diversity: 3
Activity: 29
Co-Author
Co-Institution
D-Core
- 合作者
- 学生
- 导师
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn