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pro vyhledávání: '"Galgiani, John N."'
In medicine, machine learning (ML) datasets are often built using the International Classification of Diseases (ICD) codes. As new models are being developed, there is a need for larger datasets. However, ICD codes are intended for billing. We aim to
Externí odkaz:
http://arxiv.org/abs/2407.07997
Autor:
Galgiani, John N., Ampel, Neil M., Blair, Janis E., Catanzaro, Antonino, Geertsma, Francesca, Hoover, Susan E., Johnson, Royce H., Kusne, Shimon, Lisse, Jeffrey, MacDonald, Joel D., Meyerson, Shari L., Raksin, Patricia B., Siever, John, Stevens, David A., Sunenshine, Rebecca, Theodore, Nicholas
It is important to realize that guidelines cannot always account for individual variation among patients. They are not intended to supplant physician judgment with respect to particular patients or special clinical situations. Infectious Diseases Soc
Externí odkaz:
http://hdl.handle.net/10150/621661
http://arizona.openrepository.com/arizona/handle/10150/621661
http://arizona.openrepository.com/arizona/handle/10150/621661
Autor:
Galgiani, John N., Ampel, Neil M., Blair, Janis E., Catanzaro, Antonino, Geertsma, Francesca, Hoover, Susan E., Johnson, Royce H., Kusne, Shimon, Lisse, Jeffrey, MacDonald, Joel D., Meyerson, Shari L., Raksin, Patricia B., Siever, John, Stevens, David A., Sunenshine, Rebecca, Theodore, Nicholas
It is important to realize that guidelines cannot always account for individual variation among patients. They are not intended to supplant physician judgment with respect to particular patients or special clinical situations. Infectious Diseases Soc
Externí odkaz:
http://hdl.handle.net/10150/622157
http://arizona.openrepository.com/arizona/handle/10150/622157
http://arizona.openrepository.com/arizona/handle/10150/622157
Autor:
Galgiani, John N., Lang, Anqi, Howard, Brandon J., Pu, Jie, Ruberto, Irene, Koski, Lia, Collins, Jennifer, Rios, Esteban, Williamson, Thomas
Publikováno v:
In The American Journal of Medicine April 2024
Akademický článek
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Akademický článek
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Autor:
Galgiani, John N.1,2,3,4 (AUTHOR) danielpowell@arizona.edu, Hsu, Amy P.5 (AUTHOR) twins@niaid.nih.gov, Powell, Daniel A.1,4 (AUTHOR), Vyas, Jatin M.6,7 (AUTHOR) jvyas@mgh.harvard.edu, Holland, Steven M.5 (AUTHOR) sholland@niaid.nih.gov
Publikováno v:
Journal of Fungi. May2023, Vol. 9 Issue 5, p554. 15p.
Nikkomycin Z (NikZ) is a chitin synthase inhibitor with antifungal efficacy against Coccidioides spp. and other endemic fungi. Dogs suffer a rate and range of natural coccidioidomycosis similar to humans and were considered an excellent model for ini
Externí odkaz:
http://hdl.handle.net/10150/621447
http://arizona.openrepository.com/arizona/handle/10150/621447
http://arizona.openrepository.com/arizona/handle/10150/621447
Autor:
Peng, Tao, Zong, Yue, Johnson, Michael DL, Menghani, Sanjay V., Lewis, Maria Lourdes, Galgiani, John N
Publikováno v:
In Diagnostic Microbiology & Infectious Disease January 2021 99(1)
Autor:
Koehler, Megan A., Song, Lusheng, Grill, Francisca J., Shubitz, Lisa F., Powell, Daniel A., Galgiani, John N., Orbach, Marc J., Robb, Edward J., Chung, Yunro, Williams, Stacy A., Murugan, Vel, Park, Jin-gyoon, LaBaer, Joshua, Lake, Douglas F., Magee, D. Mitchell
Publikováno v:
Journal of Fungi; May2024, Vol. 10 Issue 5, p307, 9p