Zobrazeno 1 - 10
of 223
pro vyhledávání: '"Banda, Juan"'
Autor:
Callahan, Alison, McElfresh, Duncan, Banda, Juan M., Bunney, Gabrielle, Char, Danton, Chen, Jonathan, Corbin, Conor K., Dash, Debadutta, Downing, Norman L., Jain, Sneha S., Kotecha, Nikesh, Masterson, Jonathan, Mello, Michelle M., Morse, Keith, Nallan, Srikar, Pandya, Abby, Revri, Anurang, Sharma, Aditya, Sharp, Christopher, Thapa, Rahul, Wornow, Michael, Youssef, Alaa, Pfeffer, Michael A., Shah, Nigam H.
The impact of using artificial intelligence (AI) to guide patient care or operational processes is an interplay of the AI model's output, the decision-making protocol based on that output, and the capacity of the stakeholders involved to take the nec
Externí odkaz:
http://arxiv.org/abs/2403.07911
Autor:
Tekumalla, Ramya, Banda, Juan M.
The COVID-19 pandemic has presented significant challenges to the healthcare industry and society as a whole. With the rapid development of COVID-19 vaccines, social media platforms have become a popular medium for discussions on vaccine-related topi
Externí odkaz:
http://arxiv.org/abs/2309.06503
Autor:
Dash, Debadutta, Thapa, Rahul, Banda, Juan M., Swaminathan, Akshay, Cheatham, Morgan, Kashyap, Mehr, Kotecha, Nikesh, Chen, Jonathan H., Gombar, Saurabh, Downing, Lance, Pedreira, Rachel, Goh, Ethan, Arnaout, Angel, Morris, Garret Kenn, Magon, Honor, Lungren, Matthew P, Horvitz, Eric, Shah, Nigam H.
Despite growing interest in using large language models (LLMs) in healthcare, current explorations do not assess the real-world utility and safety of LLMs in clinical settings. Our objective was to determine whether two LLMs can serve information nee
Externí odkaz:
http://arxiv.org/abs/2304.13714
Autor:
Tekumalla, Ramya, Banda, Juan M.
Supervised learning algorithms are heavily reliant on annotated datasets to train machine learning models. However, the curation of the annotated datasets is laborious and time consuming due to the manual effort involved and has become a huge bottlen
Externí odkaz:
http://arxiv.org/abs/2209.12614
Autor:
Callahan, Tiffany J., Stefanski, Adrianne L., Wyrwa, Jordan M., Zeng, Chenjie, Ostropolets, Anna, Banda, Juan M., Baumgartner Jr., William A., Boyce, Richard D., Casiraghi, Elena, Coleman, Ben D., Collins, Janine H., Deakyne-Davies, Sara J., Feinstein, James A., Haendel, Melissa A., Lin, Asiyah Y., Martin, Blake, Matentzoglu, Nicolas A., Meeker, Daniella, Reese, Justin, Sinclair, Jessica, Taneja, Sanya B., Trinkley, Katy E., Vasilevsky, Nicole A., Williams, Andrew, Zhang, Xingman A., Denny, Joshua C., Robinson, Peter N., Ryan, Patrick, Hripcsak, George, Bennett, Tellen D., Hunter, Lawrence E., Kahn, Michael G.
Background: Common data models solve many challenges of standardizing electronic health record (EHR) data, but are unable to semantically integrate all the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry o
Externí odkaz:
http://arxiv.org/abs/2209.04732
Autor:
Tekumalla, Ramya, Banda, Juan M.
Social media is often utilized as a lifeline for communication during natural disasters. Traditionally, natural disaster tweets are filtered from the Twitter stream using the name of the natural disaster and the filtered tweets are sent for human ann
Externí odkaz:
http://arxiv.org/abs/2207.04947
Autor:
Banda, Juan
Publikováno v:
Montana State University.
With the launch of NASA's Solar Dynamics Observatory mission, a whole new age of high-quality solar image analysis was started. With the generation of over 1.5 Terabytes of solar images, per day, that are ten times higher resolution than high-definit
Externí odkaz:
http://etd.lib.montana.edu/etd/2011/banda/BandaJ0511.pdf
The use of social media data, like Twitter, for biomedical research has been gradually increasing over the years. With the COVID-19 pandemic, researchers have turned to more nontraditional sources of clinical data to characterize the disease in near
Externí odkaz:
http://arxiv.org/abs/2107.12565
The rapid evolution of the COVID-19 pandemic has underscored the need to quickly disseminate the latest clinical knowledge during a public-health emergency. One surprisingly effective platform for healthcare professionals (HCPs) to share knowledge an
Externí odkaz:
http://arxiv.org/abs/2102.06836
Autor:
Tekumalla, Ramya, Banda, Juan M.
Since the classification of COVID-19 as a global pandemic, there have been many attempts to treat and contain the virus. Although there is no specific antiviral treatment recommended for COVID-19, there are several drugs that can potentially help wit
Externí odkaz:
http://arxiv.org/abs/2007.10276