Zobrazeno 1 - 10
of 1 300
pro vyhledávání: '"Butte, A. J."'
Autor:
Sun, Shenghuan, Goldgof, Gregory M., Schubert, Alexander, Sun, Zhiqing, Hartvigsen, Thomas, Butte, Atul J., Alaa, Ahmed
Vision-Language Models (VLM) can support clinicians by analyzing medical images and engaging in natural language interactions to assist in diagnostic and treatment tasks. However, VLMs often exhibit "hallucinogenic" behavior, generating textual outpu
Externí odkaz:
http://arxiv.org/abs/2405.19567
Autor:
Miao, Brenda Y., Chen, Irene Y., Williams, Christopher YK, Davidson, Jaysón, Garcia-Agundez, Augusto, Sun, Shenghuan, Zack, Travis, Saria, Suchi, Arnaout, Rima, Quer, Giorgio, Sadaei, Hossein J., Torkamani, Ali, Beaulieu-Jones, Brett, Yu, Bin, Gianfrancesco, Milena, Butte, Atul J., Norgeot, Beau, Sushil, Madhumita
Recent advances in generative models, including large language models (LLMs), vision language models (VLMs), and diffusion models, have accelerated the field of natural language and image processing in medicine and marked a significant paradigm shift
Externí odkaz:
http://arxiv.org/abs/2403.02558
Autor:
Miao, Brenda Y., Williams, Christopher YK, Chinedu-Eneh, Ebenezer, Zack, Travis, Alsentzer, Emily, Butte, Atul J., Chen, Irene Y.
Prescription contraceptives play a critical role in supporting women's reproductive health. With nearly 50 million women in the United States using contraceptives, understanding the factors that drive contraceptives selection and switching is of sign
Externí odkaz:
http://arxiv.org/abs/2402.03597
Autor:
Sushil, Madhumita, Zack, Travis, Mandair, Divneet, Zheng, Zhiwei, Wali, Ahmed, Yu, Yan-Ning, Quan, Yuwei, Butte, Atul J.
Although supervised machine learning is popular for information extraction from clinical notes, creating large annotated datasets requires extensive domain expertise and is time-consuming. Meanwhile, large language models (LLMs) have demonstrated pro
Externí odkaz:
http://arxiv.org/abs/2401.13887
Autor:
Huang, Yu-Ning, Love, Michael I., Ronkowski, Cynthia Flaire, Deshpande, Dhrithi, Schriml, Lynn M., Wong-Beringer, Annie, Mons, Barend, Corbett-Detig, Russell, Hunter, Christopher I, Moore, Jason H., Garmire, Lana X., Reddy, T. B. K., Hide, Winston A., Butte, Atul J., Robinson, Mark D., Mangul, Serghei
Metadata, often termed "data about data," is crucial for organizing, understanding, and managing vast omics datasets. It aids in efficient data discovery, integration, and interpretation, enabling users to access, comprehend, and utilize data effecti
Externí odkaz:
http://arxiv.org/abs/2401.02965
Autor:
Mehandru, Nikita, Miao, Brenda Y., Almaraz, Eduardo Rodriguez, Sushil, Madhumita, Butte, Atul J., Alaa, Ahmed
Recent developments in large language models (LLMs) have unlocked new opportunities for healthcare, from information synthesis to clinical decision support. These new LLMs are not just capable of modeling language, but can also act as intelligent "ag
Externí odkaz:
http://arxiv.org/abs/2309.10895
Autor:
Sushil, Madhumita, Kennedy, Vanessa E., Mandair, Divneet, Miao, Brenda Y., Zack, Travis, Butte, Atul J.
Both medical care and observational studies in oncology require a thorough understanding of a patient's disease progression and treatment history, often elaborately documented in clinical notes. Despite their vital role, no current oncology informati
Externí odkaz:
http://arxiv.org/abs/2308.03853
We aimed to investigate the impact of social circumstances on cancer therapy selection using natural language processing to derive insights from social worker documentation. We developed and employed a Bidirectional Encoder Representations from Trans
Externí odkaz:
http://arxiv.org/abs/2306.09877
Autor:
Sushil, Madhumita, Butte, Atul J., Schuit, Ewoud, van Smeden, Maarten, Leeuwenberg, Artuur M.
Objective: Text mining of clinical notes embedded in electronic medical records is increasingly used to extract patient characteristics otherwise not or only partly available, to assess their association with relevant health outcomes. As manual data
Externí odkaz:
http://arxiv.org/abs/2301.06570
Most research studying social determinants of health (SDoH) has focused on physician notes or structured elements of the electronic medical record (EMR). We hypothesize that clinical notes from social workers, whose role is to ameliorate social and e
Externí odkaz:
http://arxiv.org/abs/2212.01462