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pro vyhledávání: '"Bumgardner, V. K. Cody"'
Autor:
Mullen, Aaron D., Harris, Daniel, Rock, Peter, Slavova, Svetla, Talbert, Jeffery, Bumgardner, V. K. Cody
We present efforts in the fields of machine learning and time series forecasting to accurately predict counts of future opioid overdose incidents recorded by Emergency Medical Services (EMS) in the state of Kentucky. Forecasts are useful to state gov
Externí odkaz:
http://arxiv.org/abs/2410.16500
Autor:
Klusty, Mitchell A., Logan, W. Vaiden, Armstrong, Samuel E., Mullen, Aaron D., Leach, Caroline N., Talbert, Jeff, Bumgardner, V. K. Cody
Administrative documentation is a major driver of rising healthcare costs and is linked to adverse outcomes, including physician burnout and diminished quality of care. This paper introduces a secure system that applies recent advancements in speech-
Externí odkaz:
http://arxiv.org/abs/2409.15378
Autor:
Mullen, Aaron, Armstrong, Samuel E., Perdeh, Jasmine, Bauer, Bjorn, Talbert, Jeffrey, Bumgardner, V. K. Cody
A multi-modal machine learning system uses multiple unique data sources and types to improve its performance. This article proposes a system that combines results from several types of models, all of which are trained on different data signals. As an
Externí odkaz:
http://arxiv.org/abs/2402.00965
Autor:
Bumgardner, V. K. Cody, Klusty, Mitchell A., Logan, W. Vaiden, Armstrong, Samuel E., Hickey, Caylin, Talbert, Jeff
This paper introduces a user-friendly platform developed by the University of Kentucky Center for Applied AI, designed to make large, customized language models (LLMs) more accessible. By capitalizing on recent advancements in multi-LoRA inference, t
Externí odkaz:
http://arxiv.org/abs/2402.00913
Machine learning classification problems are widespread in bioinformatics, but the technical knowledge required to perform model training, optimization, and inference can prevent researchers from utilizing this technology. This article presents an au
Externí odkaz:
http://arxiv.org/abs/2310.03618
This paper introduces an approach that combines the language reasoning capabilities of large language models (LLMs) with the benefits of local training to tackle complex, domain-specific tasks. Specifically, the authors demonstrate their approach by
Externí odkaz:
http://arxiv.org/abs/2308.01727
Autor:
Armstrong, Samuel E., Klusty, Mitchell A., Mullen, Aaron D., Talbert, Jeffery C., Bumgardner, V. K. Cody
Developing and enforcing study protocols is crucial in medical research, especially as interactions with participants become more intricate. Traditional rules-based systems struggle to provide the automation and flexibility required for real-time, pe
Externí odkaz:
http://arxiv.org/abs/2305.04411
Autor:
Cotter, Daniel, Bumgardner, V. K. Cody
In the past decade, the healthcare industry has made significant advances in the digitization of patient information. However, a lack of interoperability among healthcare systems still imposes a high cost to patients, hospitals, and insurers. Current
Externí odkaz:
http://arxiv.org/abs/1912.00423
The use of edge computing can be extremely valuable in support of CPS efforts. However, few if any testbeds provide the type of resource control and provisioning required to support edge-enabled CPS experimentation. Likewise, commercial offerings pro
Externí odkaz:
http://arxiv.org/abs/1910.01173
Publikováno v:
AMIA Jt Summits Transl Sci Proc
Digital pathology applications present several challenges, including the processing, storage, and distribution of gigapixel images across distributed computational resources and viewing stations. Individual slides must be available for interactive re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::a67f312e31a362c468d78e71a2e144c1
https://europepmc.org/articles/PMC10283146/
https://europepmc.org/articles/PMC10283146/