Zobrazeno 1 - 10
of 2 213
pro vyhledávání: '"Hong, Chuan"'
Autor:
Li, Siqi, Wu, Qiming, Li, Xin, Miao, Di, Hong, Chuan, Gu, Wenjun, Shang, Yuqing, Okada, Yohei, Chen, Michael Hao, Yan, Mengying, Ning, Yilin, Ong, Marcus Eng Hock, Liu, Nan
Objective: Mitigating algorithmic disparities is a critical challenge in healthcare research, where ensuring equity and fairness is paramount. While large-scale healthcare data exist across multiple institutions, cross-institutional collaborations of
Externí odkaz:
http://arxiv.org/abs/2410.17269
Autor:
Li, Siqi, Li, Xin, Yu, Kunyu, Miao, Di, Zhu, Mingcheng, Yan, Mengying, Ke, Yuhe, D'Agostino, Danny, Ning, Yilin, Wu, Qiming, Wang, Ziwen, Shang, Yuqing, Liu, Molei, Hong, Chuan, Liu, Nan
Clinical and biomedical research in low-resource settings often faces significant challenges due to the need for high-quality data with sufficient sample sizes to construct effective models. These constraints hinder robust model training and prompt r
Externí odkaz:
http://arxiv.org/abs/2407.11034
Autor:
Yang, Rui, Ning, Yilin, Keppo, Emilia, Liu, Mingxuan, Hong, Chuan, Bitterman, Danielle S, Ong, Jasmine Chiat Ling, Ting, Daniel Shu Wei, Liu, Nan
Generative artificial intelligence (AI) has brought revolutionary innovations in various fields, including medicine. However, it also exhibits limitations. In response, retrieval-augmented generation (RAG) provides a potential solution, enabling mode
Externí odkaz:
http://arxiv.org/abs/2406.12449
Autor:
Gao, Jianhui, Chou, Benson, McCaw, Zachary R., Thurston, Hilary, Varghese, Paul, Hong, Chuan, Gronsbell, Jessica
Ensuring that machine learning (ML) models are safe, effective, and equitable across all patient groups is essential for clinical decision-making and for preventing the reinforcement of existing health disparities. This review examines notions of fai
Externí odkaz:
http://arxiv.org/abs/2406.09307
Conditional independence tests are crucial across various disciplines in determining the independence of an outcome variable $Y$ from a treatment variable $X$, conditioning on a set of confounders $Z$. The Conditional Randomization Test (CRT) offers
Externí odkaz:
http://arxiv.org/abs/2405.19231
Publikováno v:
A&A 689, A293 (2024)
From the IllustrisTNG-50 simulation, a sample of 836 central disk galaxies with tiny stellar halos is chosen to study the inherent evolution of galaxies driven by nature. These galaxies are classified as compact, normal, or extended by referencing th
Externí odkaz:
http://arxiv.org/abs/2404.10432
With the increasing availability of electronic health records (EHR) linked with biobank data for translational research, a critical step in realizing its potential is to accurately classify phenotypes for patients. Existing approaches to achieve this
Externí odkaz:
http://arxiv.org/abs/2404.01191
Autor:
Yuan, Han, Hong, Chuan, Jiang, Pengtao, Zhao, Gangming, Tran, Nguyen Tuan Anh, Xu, Xinxing, Yan, Yet Yen, Liu, Nan
Background: Pneumothorax is an acute thoracic disease caused by abnormal air collection between the lungs and chest wall. To address the opaqueness often associated with deep learning (DL) models, explainable artificial intelligence (XAI) methods hav
Externí odkaz:
http://arxiv.org/abs/2403.18871
Publikováno v:
A&A 686, A168 (2024)
Utilizing a kinematic decomposition of simulated galaxies, we focus on galaxies with tiny kinematically inferred stellar halos, indicative of weak external influences. We investigate the intricate interplay between internal (natural) and external (nu
Externí odkaz:
http://arxiv.org/abs/2403.17313
Autor:
Li, Siqi, Shang, Yuqing, Wang, Ziwen, Wu, Qiming, Hong, Chuan, Ning, Yilin, Miao, Di, Ong, Marcus Eng Hock, Chakraborty, Bibhas, Liu, Nan
Survival analysis serves as a fundamental component in numerous healthcare applications, where the determination of the time to specific events (such as the onset of a certain disease or death) for patients is crucial for clinical decision-making. Sc
Externí odkaz:
http://arxiv.org/abs/2403.05229