Zobrazeno 1 - 10
of 539
pro vyhledávání: '"Chen, Christina A"'
Autor:
Baur, Sebastien, Nabulsi, Zaid, Weng, Wei-Hung, Garrison, Jake, Blankemeier, Louis, Fishman, Sam, Chen, Christina, Kakarmath, Sujay, Maimbolwa, Minyoi, Sanjase, Nsala, Shuma, Brian, Matias, Yossi, Corrado, Greg S., Patel, Shwetak, Shetty, Shravya, Prabhakara, Shruthi, Muyoyeta, Monde, Ardila, Diego
Health acoustic sounds such as coughs and breaths are known to contain useful health signals with significant potential for monitoring health and disease, yet are underexplored in the medical machine learning community. The existing deep learning sys
Externí odkaz:
http://arxiv.org/abs/2403.02522
Autor:
Xu, Shawn, Yang, Lin, Kelly, Christopher, Sieniek, Marcin, Kohlberger, Timo, Ma, Martin, Weng, Wei-Hung, Kiraly, Atilla, Kazemzadeh, Sahar, Melamed, Zakkai, Park, Jungyeon, Strachan, Patricia, Liu, Yun, Lau, Chuck, Singh, Preeti, Chen, Christina, Etemadi, Mozziyar, Kalidindi, Sreenivasa Raju, Matias, Yossi, Chou, Katherine, Corrado, Greg S., Shetty, Shravya, Tse, Daniel, Prabhakara, Shruthi, Golden, Daniel, Pilgrim, Rory, Eswaran, Krish, Sellergren, Andrew
In this work, we present an approach, which we call Embeddings for Language/Image-aligned X-Rays, or ELIXR, that leverages a language-aligned image encoder combined or grafted onto a fixed LLM, PaLM 2, to perform a broad range of chest X-ray tasks. W
Externí odkaz:
http://arxiv.org/abs/2308.01317
Autor:
Weng, Wei-Hung, Baur, Sebastien, Daswani, Mayank, Chen, Christina, Harrell, Lauren, Kakarmath, Sujay, Jabara, Mariam, Behsaz, Babak, McLean, Cory Y., Matias, Yossi, Corrado, Greg S., Shetty, Shravya, Prabhakara, Shruthi, Liu, Yun, Danaei, Goodarz, Ardila, Diego
Cardiovascular diseases (CVDs) are responsible for a large proportion of premature deaths in low- and middle-income countries. Early CVD detection and intervention is critical in these populations, yet many existing CVD risk scores require a physical
Externí odkaz:
http://arxiv.org/abs/2305.05648
Chronic kidney disease (CKD) represents a slowly progressive disorder that can eventually require renal replacement therapy (RRT) including dialysis or renal transplantation. Early identification of patients who will require RRT (as much as 1 year in
Externí odkaz:
http://arxiv.org/abs/2209.01469
Autor:
Babenko, Boris, Traynis, Ilana, Chen, Christina, Singh, Preeti, Uddin, Akib, Cuadros, Jorge, Daskivich, Lauren P., Maa, April Y., Kim, Ramasamy, Kang, Eugene Yu-Chuan, Matias, Yossi, Corrado, Greg S., Peng, Lily, Webster, Dale R., Semturs, Christopher, Krause, Jonathan, Varadarajan, Avinash V., Hammel, Naama, Liu, Yun
External eye photos were recently shown to reveal signs of diabetic retinal disease and elevated HbA1c. In this paper, we evaluate if external eye photos contain information about additional systemic medical conditions. We developed a deep learning s
Externí odkaz:
http://arxiv.org/abs/2207.08998
Autor:
Loreaux, Eric, Yu, Ke, Kemp, Jonas, Seneviratne, Martin, Chen, Christina, Roy, Subhrajit, Protsyuk, Ivan, Harris, Natalie, D'Amour, Alexander, Yadlowsky, Steve, Chen, Ming-Jun
Machine learning systems show significant promise for forecasting patient adverse events via risk scores. However, these risk scores implicitly encode assumptions about future interventions that the patient is likely to receive, based on the interven
Externí odkaz:
http://arxiv.org/abs/2207.02941
Autor:
Roy, Subhrajit, Mincu, Diana, Proleev, Lev, Rostamzadeh, Negar, Ghate, Chintan, Harris, Natalie, Chen, Christina, Schrouff, Jessica, Tomasev, Nenad, Hartsell, Fletcher Lee, Heller, Katherine
Literature on machine learning for multiple sclerosis has primarily focused on the use of neuroimaging data such as magnetic resonance imaging and clinical laboratory tests for disease identification. However, studies have shown that these modalities
Externí odkaz:
http://arxiv.org/abs/2204.03969
Enabling faster and more reliable sonographic assessment of gestational age through machine learning
Autor:
Lee, Chace, Willis, Angelica, Chen, Christina, Sieniek, Marcin, Uddin, Akib, Wong, Jonny, Pilgrim, Rory, Chou, Katherine, Tse, Daniel, Shetty, Shravya, Gomes, Ryan G.
Fetal ultrasounds are an essential part of prenatal care and can be used to estimate gestational age (GA). Accurate GA assessment is important for providing appropriate prenatal care throughout pregnancy and identifying complications such as fetal gr
Externí odkaz:
http://arxiv.org/abs/2203.11903
Autor:
Gomes, Ryan G., Vwalika, Bellington, Lee, Chace, Willis, Angelica, Sieniek, Marcin, Price, Joan T., Chen, Christina, Kasaro, Margaret P., Taylor, James A., Stringer, Elizabeth M., McKinney, Scott Mayer, Sindano, Ntazana, Dahl, George E., Goodnight III, William, Gilmer, Justin, Chi, Benjamin H., Lau, Charles, Spitz, Terry, Saensuksopa, T, Liu, Kris, Wong, Jonny, Pilgrim, Rory, Uddin, Akib, Corrado, Greg, Peng, Lily, Chou, Katherine, Tse, Daniel, Stringer, Jeffrey S. A., Shetty, Shravya
Despite considerable progress in maternal healthcare, maternal and perinatal deaths remain high in low-to-middle income countries. Fetal ultrasound is an important component of antenatal care, but shortage of adequately trained healthcare workers has
Externí odkaz:
http://arxiv.org/abs/2203.10139
Autor:
Schrouff, Jessica, Harris, Natalie, Koyejo, Oluwasanmi, Alabdulmohsin, Ibrahim, Schnider, Eva, Opsahl-Ong, Krista, Brown, Alex, Roy, Subhrajit, Mincu, Diana, Chen, Christina, Dieng, Awa, Liu, Yuan, Natarajan, Vivek, Karthikesalingam, Alan, Heller, Katherine, Chiappa, Silvia, D'Amour, Alexander
Publikováno v:
Advances in Neural Information Processing Systems 35 (NeurIPS 2022)
Diagnosing and mitigating changes in model fairness under distribution shift is an important component of the safe deployment of machine learning in healthcare settings. Importantly, the success of any mitigation strategy strongly depends on the stru
Externí odkaz:
http://arxiv.org/abs/2202.01034