Zobrazeno 1 - 10
of 762
pro vyhledávání: '"Kalpathy‐Cramer, Jayashree"'
Autor:
Idnay, Betina, Xu, Zihan, Adams, William G., Adibuzzaman, Mohammad, Anderson, Nicholas R., Bahroos, Neil, Bell, Douglas S., Bumgardner, Cody, Campion, Thomas, Castro, Mario, Cimino, James J., Cohen, I. Glenn, Dorr, David, Elkin, Peter L, Fan, Jungwei W., Ferris, Todd, Foran, David J., Hanauer, David, Hogarth, Mike, Huang, Kun, Kalpathy-Cramer, Jayashree, Kandpal, Manoj, Karnik, Niranjan S., Katoch, Avnish, Lai, Albert M., Lambert, Christophe G., Li, Lang, Lindsell, Christopher, Liu, Jinze, Lu, Zhiyong, Luo, Yuan, McGarvey, Peter, Mendonca, Eneida A., Mirhaji, Parsa, Murphy, Shawn, Osborne, John D., Paschalidis, Ioannis C., Harris, Paul A., Prior, Fred, Shaheen, Nicholas J., Shara, Nawar, Sim, Ida, Tachinardi, Umberto, Waitman, Lemuel R., Wright, Rosalind J., Zai, Adrian H., Zheng, Kai, Lee, Sandra Soo-Jin, Malin, Bradley A., Natarajan, Karthik, Price II, W. Nicholson, Zhang, Rui, Zhang, Yiye, Xu, Hua, Bian, Jiang, Weng, Chunhua, Peng, Yifan
This study reports a comprehensive environmental scan of the generative AI (GenAI) infrastructure in the national network for clinical and translational science across 36 institutions supported by the Clinical and Translational Science Award (CTSA) P
Externí odkaz:
http://arxiv.org/abs/2410.12793
Autor:
Schmidt, Kendall, Bearce, Benjamin, Chang, Ken, Coombs, Laura, Farahani, Keyvan, Elbatele, Marawan, Mouhebe, Kaouther, Marti, Robert, Zhang, Ruipeng, Zhang, Yao, Wang, Yanfeng, Hu, Yaojun, Ying, Haochao, Xu, Yuyang, Testagrose, Conrad, Demirer, Mutlu, Gupta, Vikash, Akünal, Ünal, Bujotzek, Markus, Maier-Hein, Klaus H., Qin, Yi, Li, Xiaomeng, Kalpathy-Cramer, Jayashree, Roth, Holger R.
Publikováno v:
Medical Image Analysis Volume 95, July 2024, 103206
The correct interpretation of breast density is important in the assessment of breast cancer risk. AI has been shown capable of accurately predicting breast density, however, due to the differences in imaging characteristics across mammography system
Externí odkaz:
http://arxiv.org/abs/2405.14900
Autor:
Gonçalves, Tiago, Pulido-Arias, Dagoberto, Willett, Julian, Hoebel, Katharina V., Cleveland, Mason, Ahmed, Syed Rakin, Gerstner, Elizabeth, Kalpathy-Cramer, Jayashree, Cardoso, Jaime S., Bridge, Christopher P., Kim, Albert E.
The interactions between tumor cells and the tumor microenvironment (TME) dictate therapeutic efficacy of radiation and many systemic therapies in breast cancer. However, to date, there is not a widely available method to reproducibly measure tumor a
Externí odkaz:
http://arxiv.org/abs/2404.16397
Autor:
Lorenzo, Guillermo, Ahmed, Syed Rakin, Hormuth II, David A., Vaughn, Brenna, Kalpathy-Cramer, Jayashree, Solorio, Luis, Yankeelov, Thomas E., Gomez, Hector
Despite the remarkable advances in cancer diagnosis, treatment, and management that have occurred over the past decade, malignant tumors remain a major public health problem. Further progress in combating cancer may be enabled by personalizing the de
Externí odkaz:
http://arxiv.org/abs/2308.14925
Autor:
Lekadir, Karim, Feragen, Aasa, Fofanah, Abdul Joseph, Frangi, Alejandro F, Buyx, Alena, Emelie, Anais, Lara, Andrea, Porras, Antonio R, Chan, An-Wen, Navarro, Arcadi, Glocker, Ben, Botwe, Benard O, Khanal, Bishesh, Beger, Brigit, Wu, Carol C, Cintas, Celia, Langlotz, Curtis P, Rueckert, Daniel, Mzurikwao, Deogratias, Fotiadis, Dimitrios I, Zhussupov, Doszhan, Ferrante, Enzo, Meijering, Erik, Weicken, Eva, González, Fabio A, Asselbergs, Folkert W, Prior, Fred, Krestin, Gabriel P, Collins, Gary, Tegenaw, Geletaw S, Kaissis, Georgios, Misuraca, Gianluca, Tsakou, Gianna, Dwivedi, Girish, Kondylakis, Haridimos, Jayakody, Harsha, Woodruf, Henry C, Mayer, Horst Joachim, Aerts, Hugo JWL, Walsh, Ian, Chouvarda, Ioanna, Buvat, Irène, Tributsch, Isabell, Rekik, Islem, Duncan, James, Kalpathy-Cramer, Jayashree, Zahir, Jihad, Park, Jinah, Mongan, John, Gichoya, Judy W, Schnabel, Julia A, Kushibar, Kaisar, Riklund, Katrine, Mori, Kensaku, Marias, Kostas, Amugongo, Lameck M, Fromont, Lauren A, Maier-Hein, Lena, Alberich, Leonor Cerdá, Rittner, Leticia, Phiri, Lighton, Marrakchi-Kacem, Linda, Donoso-Bach, Lluís, Martí-Bonmatí, Luis, Cardoso, M Jorge, Bobowicz, Maciej, Shabani, Mahsa, Tsiknakis, Manolis, Zuluaga, Maria A, Bielikova, Maria, Fritzsche, Marie-Christine, Camacho, Marina, Linguraru, Marius George, Wenzel, Markus, De Bruijne, Marleen, Tolsgaard, Martin G, Ghassemi, Marzyeh, Ashrafuzzaman, Md, Goisauf, Melanie, Yaqub, Mohammad, Abadía, Mónica Cano, Mahmoud, Mukhtar M E, Elattar, Mustafa, Rieke, Nicola, Papanikolaou, Nikolaos, Lazrak, Noussair, Díaz, Oliver, Salvado, Olivier, Pujol, Oriol, Sall, Ousmane, Guevara, Pamela, Gordebeke, Peter, Lambin, Philippe, Brown, Pieta, Abolmaesumi, Purang, Dou, Qi, Lu, Qinghua, Osuala, Richard, Nakasi, Rose, Zhou, S Kevin, Napel, Sandy, Colantonio, Sara, Albarqouni, Shadi, Joshi, Smriti, Carter, Stacy, Klein, Stefan, Petersen, Steffen E, Aussó, Susanna, Awate, Suyash, Raviv, Tammy Riklin, Cook, Tessa, Mutsvangwa, Tinashe E M, Rogers, Wendy A, Niessen, Wiro J, Puig-Bosch, Xènia, Zeng, Yi, Mohammed, Yunusa G, Aquino, Yves Saint James, Salahuddin, Zohaib, Starmans, Martijn P A
Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinica
Externí odkaz:
http://arxiv.org/abs/2309.12325
Autor:
Hoebel, Katharina V., Lemay, Andreanne, Campbell, John Peter, Ostmo, Susan, Chiang, Michael F., Bridge, Christopher P., Li, Matthew D., Singh, Praveer, Coyner, Aaron S., Kalpathy-Cramer, Jayashree
Many variables of interest in clinical medicine, like disease severity, are recorded using discrete ordinal categories such as normal/mild/moderate/severe. These labels are used to train and evaluate disease severity prediction models. However, ordin
Externí odkaz:
http://arxiv.org/abs/2305.19097
Autor:
Whitney, Heather M., Baughan, Natalie, Myers, Kyle J., Drukker, Karen, Gichoya, Judy, Bower, Brad, Chen, Weijie, Gruszauskas, Nicholas, Kalpathy-Cramer, Jayashree, Koyejo, Sanmi, Sá, Rui C., Sahiner, Berkman, Zhang, Zi, Giger, Maryellen L.
Purpose: The Medical Imaging and Data Resource Center (MIDRC) open data commons was launched to accelerate the development of artificial intelligence (AI) algorithms to help address the COVID-19 pandemic. The purpose of this study was to quantify lon
Externí odkaz:
http://arxiv.org/abs/2303.10501
Autor:
Cardoso, M. Jorge, Li, Wenqi, Brown, Richard, Ma, Nic, Kerfoot, Eric, Wang, Yiheng, Murrey, Benjamin, Myronenko, Andriy, Zhao, Can, Yang, Dong, Nath, Vishwesh, He, Yufan, Xu, Ziyue, Hatamizadeh, Ali, Zhu, Wentao, Liu, Yun, Zheng, Mingxin, Tang, Yucheng, Yang, Isaac, Zephyr, Michael, Hashemian, Behrooz, Alle, Sachidanand, Darestani, Mohammad Zalbagi, Budd, Charlie, Modat, Marc, Vercauteren, Tom, Wang, Guotai, Li, Yiwen, Hu, Yipeng, Fu, Yunguan, Gorman, Benjamin, Johnson, Hans, Genereaux, Brad, Erdal, Barbaros S., Gupta, Vikash, Diaz-Pinto, Andres, Dourson, Andre, Maier-Hein, Lena, Jaeger, Paul F., Baumgartner, Michael, Kalpathy-Cramer, Jayashree, Flores, Mona, Kirby, Justin, Cooper, Lee A. D., Roth, Holger R., Xu, Daguang, Bericat, David, Floca, Ralf, Zhou, S. Kevin, Shuaib, Haris, Farahani, Keyvan, Maier-Hein, Klaus H., Aylward, Stephen, Dogra, Prerna, Ourselin, Sebastien, Feng, Andrew
Artificial Intelligence (AI) is having a tremendous impact across most areas of science. Applications of AI in healthcare have the potential to improve our ability to detect, diagnose, prognose, and intervene on human disease. For AI models to be use
Externí odkaz:
http://arxiv.org/abs/2211.02701
Autor:
Kumar, Sourav, Lakshminarayanan, A., Chang, Ken, Guretno, Feri, Mien, Ivan Ho, Kalpathy-Cramer, Jayashree, Krishnaswamy, Pavitra, Singh, Praveer
Federated Learning (FL) wherein multiple institutions collaboratively train a machine learning model without sharing data is becoming popular. Participating institutions might not contribute equally, some contribute more data, some better quality dat
Externí odkaz:
http://arxiv.org/abs/2209.05424
Estimating the test performance of software AI-based medical devices under distribution shifts is crucial for evaluating the safety, efficiency, and usability prior to clinical deployment. Due to the nature of regulated medical device software and th
Externí odkaz:
http://arxiv.org/abs/2207.05796