Zobrazeno 1 - 10
of 127
pro vyhledávání: '"Webster, Dale R"'
Autor:
Ahmed, Faruk, Sellergren, Andrew, Yang, Lin, Xu, Shawn, Babenko, Boris, Ward, Abbi, Olson, Niels, Mohtashamian, Arash, Matias, Yossi, Corrado, Greg S., Duong, Quang, Webster, Dale R., Shetty, Shravya, Golden, Daniel, Liu, Yun, Steiner, David F., Wulczyn, Ellery
Microscopic interpretation of histopathology images underlies many important diagnostic and treatment decisions. While advances in vision-language modeling raise new opportunities for analysis of such images, the gigapixel-scale size of whole slide i
Externí odkaz:
http://arxiv.org/abs/2406.19578
Autor:
Ward, Abbi, Li, Jimmy, Wang, Julie, Lakshminarasimhan, Sriram, Carrick, Ashley, Campana, Bilson, Hartford, Jay, S, Pradeep Kumar, Tiyasirichokchai, Tiya, Virmani, Sunny, Wong, Renee, Matias, Yossi, Corrado, Greg S., Webster, Dale R., Siegel, Dawn, Lin, Steven, Ko, Justin, Karthikesalingam, Alan, Semturs, Christopher, Rao, Pooja
Background: Health datasets from clinical sources do not reflect the breadth and diversity of disease in the real world, impacting research, medical education, and artificial intelligence (AI) tool development. Dermatology is a suitable area to devel
Externí odkaz:
http://arxiv.org/abs/2402.18545
Autor:
Rikhye, Rajeev V., Loh, Aaron, Hong, Grace Eunhae, Singh, Preeti, Smith, Margaret Ann, Muralidharan, Vijaytha, Wong, Doris, Sayres, Rory, Phung, Michelle, Betancourt, Nicolas, Fong, Bradley, Sahasrabudhe, Rachna, Nasim, Khoban, Eschholz, Alec, Mustafa, Basil, Freyberg, Jan, Spitz, Terry, Matias, Yossi, Corrado, Greg S., Chou, Katherine, Webster, Dale R., Bui, Peggy, Liu, Yuan, Liu, Yun, Ko, Justin, Lin, Steven
Recently, there has been great progress in the ability of artificial intelligence (AI) algorithms to classify dermatological conditions from clinical photographs. However, little is known about the robustness of these algorithms in real-world setting
Externí odkaz:
http://arxiv.org/abs/2402.15566
Autor:
Freyberg, Jan, Roy, Abhijit Guha, Spitz, Terry, Freeman, Beverly, Schaekermann, Mike, Strachan, Patricia, Schnider, Eva, Wong, Renee, Webster, Dale R, Karthikesalingam, Alan, Liu, Yun, Dvijotham, Krishnamurthy, Telang, Umesh
During the diagnostic process, doctors incorporate multimodal information including imaging and the medical history - and similarly medical AI development has increasingly become multimodal. In this paper we tackle a more subtle challenge: doctors ta
Externí odkaz:
http://arxiv.org/abs/2401.12032
Autor:
McDuff, Daniel, Schaekermann, Mike, Tu, Tao, Palepu, Anil, Wang, Amy, Garrison, Jake, Singhal, Karan, Sharma, Yash, Azizi, Shekoofeh, Kulkarni, Kavita, Hou, Le, Cheng, Yong, Liu, Yun, Mahdavi, S Sara, Prakash, Sushant, Pathak, Anupam, Semturs, Christopher, Patel, Shwetak, Webster, Dale R, Dominowska, Ewa, Gottweis, Juraj, Barral, Joelle, Chou, Katherine, Corrado, Greg S, Matias, Yossi, Sunshine, Jake, Karthikesalingam, Alan, Natarajan, Vivek
An accurate differential diagnosis (DDx) is a cornerstone of medical care, often reached through an iterative process of interpretation that combines clinical history, physical examination, investigations and procedures. Interactive interfaces powere
Externí odkaz:
http://arxiv.org/abs/2312.00164
Autor:
Lai, Jeremy, Ahmed, Faruk, Vijay, Supriya, Jaroensri, Tiam, Loo, Jessica, Vyawahare, Saurabh, Agarwal, Saloni, Jamil, Fayaz, Matias, Yossi, Corrado, Greg S., Webster, Dale R., Krause, Jonathan, Liu, Yun, Chen, Po-Hsuan Cameron, Wulczyn, Ellery, Steiner, David F.
Task-specific deep learning models in histopathology offer promising opportunities for improving diagnosis, clinical research, and precision medicine. However, development of such models is often limited by availability of high-quality data. Foundati
Externí odkaz:
http://arxiv.org/abs/2310.13259
Autor:
Stutz, David, Cemgil, Ali Taylan, Roy, Abhijit Guha, Matejovicova, Tatiana, Barsbey, Melih, Strachan, Patricia, Schaekermann, Mike, Freyberg, Jan, Rikhye, Rajeev, Freeman, Beverly, Matos, Javier Perez, Telang, Umesh, Webster, Dale R., Liu, Yuan, Corrado, Greg S., Matias, Yossi, Kohli, Pushmeet, Liu, Yun, Doucet, Arnaud, Karthikesalingam, Alan
For safety, AI systems in health undergo thorough evaluations before deployment, validating their predictions against a ground truth that is assumed certain. However, this is actually not the case and the ground truth may be uncertain. Unfortunately,
Externí odkaz:
http://arxiv.org/abs/2307.02191
Autor:
Lang, Oran, Yaya-Stupp, Doron, Traynis, Ilana, Cole-Lewis, Heather, Bennett, Chloe R., Lyles, Courtney, Lau, Charles, Irani, Michal, Semturs, Christopher, Webster, Dale R., Corrado, Greg S., Hassidim, Avinatan, Matias, Yossi, Liu, Yun, Hammel, Naama, Babenko, Boris
Publikováno v:
EBioMedicine 102 (2024)
AI models have shown promise in many medical imaging tasks. However, our ability to explain what signals these models have learned is severely lacking. Explanations are needed in order to increase the trust in AI-based models, and could enable novel
Externí odkaz:
http://arxiv.org/abs/2306.00985
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:
Azizi, Shekoofeh, Culp, Laura, Freyberg, Jan, Mustafa, Basil, Baur, Sebastien, Kornblith, Simon, Chen, Ting, MacWilliams, Patricia, Mahdavi, S. Sara, Wulczyn, Ellery, Babenko, Boris, Wilson, Megan, Loh, Aaron, Chen, Po-Hsuan Cameron, Liu, Yuan, Bavishi, Pinal, McKinney, Scott Mayer, Winkens, Jim, Roy, Abhijit Guha, Beaver, Zach, Ryan, Fiona, Krogue, Justin, Etemadi, Mozziyar, Telang, Umesh, Liu, Yun, Peng, Lily, Corrado, Greg S., Webster, Dale R., Fleet, David, Hinton, Geoffrey, Houlsby, Neil, Karthikesalingam, Alan, Norouzi, Mohammad, Natarajan, Vivek
Recent progress in Medical Artificial Intelligence (AI) has delivered systems that can reach clinical expert level performance. However, such systems tend to demonstrate sub-optimal "out-of-distribution" performance when evaluated in clinical setting
Externí odkaz:
http://arxiv.org/abs/2205.09723