基本信息
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个人简介
She has a broad range of informatics expertise including artificial intelligence and informatics in healthcare, computational biology and bioinformatics, and biomedical data science. Her research has been recognized through several awards, including the NSF CAREER Award for biomedical text mining, the NCATS Innovation Award for open health natural language processing, the AMIA Donald Lindberg Award in Informatics Innovation for context-aware artificial intelligence, and the CPRIT Established Investigator Recruitment Award. Dr. Liu’s research accomplishments have been recently featured in Mayo Clinic Advancing The Science, a CTSA Blog, and at UTHealth Houston. She has been active in several professional organizations including AMIA, IEEE, and ACM and currently a fellow in ACMI and IAHSI.
Dr. Liu would like to focus her research in advancing translational science and bringing novel health data science, informatics, and AI solutions to empower real-world data-driven research. She would like to develop those tools and resources under the “RITE-FAIR” principle (reproducible, implementable, transparent, and explainable – findable, accessible, interoperable, and reusable). “It is a critical time for researchers and scientists in the space of health data science, artificial intelligence, and informatics giving the huge potential of leveraging real-world data to advance biomedical science and transform health care.” However, she emphasizes that “such potential heavily depends on our ability to ensure scientific rigor, ethical, transparent with the goal of advancing data-driven science and achieving better health for everyone through people-centric and value-based innovations”.
Dr. Liu would like to focus her research in advancing translational science and bringing novel health data science, informatics, and AI solutions to empower real-world data-driven research. She would like to develop those tools and resources under the “RITE-FAIR” principle (reproducible, implementable, transparent, and explainable – findable, accessible, interoperable, and reusable). “It is a critical time for researchers and scientists in the space of health data science, artificial intelligence, and informatics giving the huge potential of leveraging real-world data to advance biomedical science and transform health care.” However, she emphasizes that “such potential heavily depends on our ability to ensure scientific rigor, ethical, transparent with the goal of advancing data-driven science and achieving better health for everyone through people-centric and value-based innovations”.
研究兴趣
论文共 790 篇作者统计合作学者相似作者
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AGING AND DISEASE (2025)
Sunyang Fu, Heling Jia, Maria Vassilaki,Vipina K. Keloth,Yifang Dang,Yujia Zhou,Muskan Garg,Ronald C. Petersen, Jennifer St Sauver,Sungrim Moon,Liwei Wang,Andrew Wen,
Journal of Biomedical Informatics (2024): 104623-104623
CANCER RESEARCH COMMUNICATIONSno. 2 (2024): 303-311
APPLIED SCIENCES-BASELno. 5 (2024): 1745
Darren Q Calley, Sunyang Fu, Marissa D Hamilton, Austin W Kalla, Christopher K Lee, Veronica A Rasmussen,John H Hollman,Hongfang Liu
Journal, physical therapy education (2024)
Dhruv Sarwal,Liwei Wang,Sonal Gandhi, Elham Sagheb Hossein Pour,Laurens P. Janssens,Adriana M. Delgado,Karen A. Doering, Anup Kumar Mishra,Jason D. Greenwood,Hongfang Liu,Shounak Majumder
Pancreatology (2024)
Satya S. Sahoo,Joseph M. Plasek,Hua Xu,Ozlem Uzuner,Trevor Cohen, Meliha Yetisgen,Hongfang Liu, Stephane Meystre,Yanshan Wang
AMERICAN JOURNAL OF HEMATOLOGYno. 3 (2024): 408-421
CEREBROVASCULAR DISEASESno. 1 (2023): 1-5
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