Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Aphinyanaphongs, Yin"'
Autor:
Chen, Ji, Chokshi, Sara, Hegde, Roshini, Gonzalez, Javier, Iturrate, Eduardo, Aphinyanaphongs, Yin, Mann, Devin
Publikováno v:
Journal of Medical Internet Research, Vol 22, Iss 4, p e16848 (2020)
BackgroundAlthough clinical decision support (CDS) alerts are effective reminders of best practices, their effectiveness is blunted by clinicians who fail to respond to an overabundance of inappropriate alerts. An electronic health record (EHR)–int
Externí odkaz:
https://doaj.org/article/fd003149a7c14037a6b5bf5187d065e0
Autor:
Lengerich, Benjamin J., Bordt, Sebastian, Nori, Harsha, Nunnally, Mark E., Aphinyanaphongs, Yin, Kellis, Manolis, Caruana, Rich
We show that large language models (LLMs) are remarkably good at working with interpretable models that decompose complex outcomes into univariate graph-represented components. By adopting a hierarchical approach to reasoning, LLMs can provide compre
Externí odkaz:
http://arxiv.org/abs/2308.01157
We consider a patient risk models which has access to patient features such as vital signs, lab values, and prior history but does not have access to a patient's diagnosis. For example, this occurs in a model deployed at intake time for triage purpos
Externí odkaz:
http://arxiv.org/abs/2306.17337
A key issue for all observational causal inference is that it relies on an unverifiable assumption - that observed characteristics are sufficient to proxy for treatment confounding. In this paper we argue that in medical cases these conditions are mo
Externí odkaz:
http://arxiv.org/abs/2303.07342
Treatment protocols, disease understanding, and viral characteristics changed over the course of the COVID-19 pandemic; as a result, the risks associated with patient comorbidities and biomarkers also changed. We add to the conversation regarding inf
Externí odkaz:
http://arxiv.org/abs/2211.08991
Autor:
Lengerich, Benjamin J., Nunnally, Mark E., Aphinyanaphongs, Yin, Ellington, Caleb, Caruana, Rich
Publikováno v:
In Journal of Biomedical Informatics June 2022 130
Autor:
Barrett, Tessa J. *, Bilaloglu, Seda, Cornwell, Macintosh, Burgess, Hannah M., Virginio, Vitor W., Drenkova, Kamelia, Ibrahim, Homam, Yuriditsky, Eugene, Aphinyanaphongs, Yin, Lifshitz, Mark, Xia Liang, Feng, Alejo, Julie, Smith, Grace, Pittaluga, Stefania, Rapkiewicz, Amy V., Wang, Jun, Iancu‐Rubin, Camelia, Mohr, Ian, Ruggles, Kelly, Stapleford, Kenneth A., Hochman, Judith, Berger, Jeffrey S.
Publikováno v:
In Journal of Thrombosis and Haemostasis December 2021 19(12):3139-3153
Autor:
Yang, Elisabeth, Aphinyanaphongs, Yin, Punjabi, Paawan V., Austrian, Jonathan, Wiesenfeld, Batia
Publikováno v:
AMIA Annu Symp Proc
Predictive models may be particularly beneficial to clinicians when they face uncertainty and seek to develop a mental model of disease progression, but we know little about the post-implementation effects of predictive models on clinicians’ experi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::c5271060735b5a4aabb1d411f5d2c3cd
https://europepmc.org/articles/PMC10148285/
https://europepmc.org/articles/PMC10148285/
Autor:
Koesmahargyo, Vidya, Zhang, Hao, Zhang, Jeff, Jethani, Neil, Aphinyanaphongs, Yin, Jankelson, Lior
Publikováno v:
In Heart Rhythm May 2024 21(5) Supplement:S554-S554
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