Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Kalluri, Krishna S"'
Autor:
Pang, Chao, Jiang, Xinzhuo, Pavinkurve, Nishanth Parameshwar, Kalluri, Krishna S., Minto, Elise L., Patterson, Jason, Zhang, Linying, Hripcsak, George, Gürsoy, Gamze, Elhadad, Noémie, Natarajan, Karthik
Synthetic Electronic Health Records (EHR) have emerged as a pivotal tool in advancing healthcare applications and machine learning models, particularly for researchers without direct access to healthcare data. Although existing methods, like rule-bas
Externí odkaz:
http://arxiv.org/abs/2402.04400
Autor:
Pang, Chao, Jiang, Xinzhuo, Kalluri, Krishna S, Spotnitz, Matthew, Chen, RuiJun, Perotte, Adler, Natarajan, Karthik
Publikováno v:
Proceedings of Machine Learning for Health, PMLR 158:239-260, 2021
Embedding algorithms are increasingly used to represent clinical concepts in healthcare for improving machine learning tasks such as clinical phenotyping and disease prediction. Recent studies have adapted state-of-the-art bidirectional encoder repre
Externí odkaz:
http://arxiv.org/abs/2111.08585
Autor:
Rodriguez VA; Columbia University, New York, NY., Tony S; Columbia University, New York, NY., Thangaraj P; Columbia University, New York, NY., Pang C; Columbia University, New York, NY., Kalluri KS; Columbia University, New York, NY., Jiang X; Columbia University, New York, NY., Ostropolets A; Columbia University, New York, NY., RuiJun C; Columbia University, New York, NY., Karthik N; Columbia University, New York, NY., Ryan P; Columbia University, New York, NY.
Publikováno v:
AMIA ... Annual Symposium proceedings. AMIA Symposium [AMIA Annu Symp Proc] 2021 Jan 25; Vol. 2020, pp. 1080-1089. Date of Electronic Publication: 2021 Jan 25 (Print Publication: 2020).
