Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Ujas Parikh"'
Autor:
Christina Oska, DO, Ujas Parikh, MD
Publikováno v:
Radiology Case Reports, Vol 20, Iss 1, Pp 289-291 (2025)
ABSTRACT: Erdheim Chester disease is a rare disease characterized by abnormal proliferation of histiocytes. The most commonly affected site is the long bones, while involvement of the breasts is very rare. In patients with breast involvement, a unila
Externí odkaz:
https://doaj.org/article/bb0efae0ce76472c8d996993fb7b7581
Autor:
Yiming Gao, Chloe Chhor, Ujas Parikh, Ian Karrington, Elizabeth V. Mausner, Samantha L. Heller
Publikováno v:
RadioGraphics. 40:13-27
Transgender is the umbrella term for individuals whose gender identity and/or gender expression differs from their assigned sex at birth. With the rise in patients undergoing gender-affirming hormone therapy and gender-affirming surgery, it is increa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c9d8aa9c2da2e6c7d98774c47c4c44e6
https://doi.org/10.1148/rg.2020190044
https://doi.org/10.1148/rg.2020190044
Autor:
Kristine Pysarenko, Pablo Gómez del Campo, Daniel Khapun, Alana A. Lewin, Linda Moy, Jungkyu Park, Yoel Shoshan, Sindhoora Murthy, Julia E. Goldberg, Robert Martí, Ella Barkan, Linda Du, Jakub Chłędowski, Ujas Parikh, Anastasia Plaunova, Krzysztof J. Geras, Sardius Chen, Alexandra Millet, Laura Heacock, Sushma Gaddam, Melanie Wegener, Eric H. Kim, Vadim Ratner, Beatriu Reig, Shalin Patel, Sana Hava, Jan Witowski, Stacey Wolfson, Michal Rosen-Zvi, Aviad Zlotnick, Jiyon Lee, Flora Gilboa-Solomon
Publikováno v:
Nature Machine Intelligence. 3:735-736
A new international competition aims to speed up the development of AI models that can assist radiologists in detecting suspicious lesions from hundreds of millions of pixels in 3D mammograms. The top three winning teams compare notes.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3db01a6dfb3f257c150bf6969fb0e791
https://doi.org/10.1038/s42256-021-00378-z
https://doi.org/10.1038/s42256-021-00378-z
Publikováno v:
Journal of the American College of Radiology
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::65c4951b820730a8d0868c9debfd3b9c
https://pubmed.ncbi.nlm.nih.gov/32335184
https://pubmed.ncbi.nlm.nih.gov/32335184
Publikováno v:
American Journal of Roentgenology. 210:246-255
Ductal carcinoma in situ (DCIS) is a noninvasive malignant breast disease traditionally described as a precursor lesion to invasive breast cancer. With screening mammography, DCIS now accounts for approximately 20% of newly diagnosed cancer cases. DC
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d9e95837c832842a9fd99931db8afe6
https://doi.org/10.2214/ajr.17.18778
https://doi.org/10.2214/ajr.17.18778
Publikováno v:
Journal of the American College of Radiology. 15:258-261
Team science involving multidisciplinary and multi-institutional collaboration is increasingly recognized as a means of strengthening the quality of scientific research. The aim of this study was to assess associations between various forms of collab
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::195f4ed43f8dd57ef126cbaad905cd98
https://doi.org/10.1016/j.jacr.2017.09.030
https://doi.org/10.1016/j.jacr.2017.09.030
Autor:
Naziya Samreen, Beatriu Reig, Kara Ho, Kyunghyun Cho, Jungkyu Park, Laura Heacock, Zhe Huang, Sushma Gaddam, Eric Kim, Yiming Gao, Linda Moy, Joshua D. Weinstein, Jason Phang, Nan Wu, Jiyon Lee, Yiqiu Shen, Alana A. Lewin, Masha Zorin, Ujas Parikh, Krzysztof J. Geras, S. Gene Kim, Krystal Airola, Stacey Wolfson, Hildegard B. Toth, Stephanie H Chung, Joe Katsnelson, Thibault Févry, Eralda Mema, Leng Leng Young Lin, Kristine Pysarenko, Esther Hwang, Stanisław Jastrzębski
Publikováno v:
IEEE transactions on medical imaging
We present a deep convolutional neural network for breast cancer screening exam classification, trained and evaluated on over 200,000 exams (over 1,000,000 images). Our network achieves an AUC of 0.895 in predicting whether there is a cancer in the b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53329e18a25d244b7312111ada30eecd
Publikováno v:
PET Clinics. 10:327-343
Fludeoxyglucose F 18 ((18)F-FDG) PET/CT has not been shown to offer additional benefit in the initial diagnosis of pancreatic cancer, but studies show benefit of (18)F-FDG PET/CT in initial staging and patient prognosis. There is evidence for (18)F-F
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0224acf2898940b1ffec425d5ebd05cd
https://doi.org/10.1016/j.cpet.2015.03.001
https://doi.org/10.1016/j.cpet.2015.03.001
Publikováno v:
PET clinics. 10(3)
Fludeoxyglucose F 18 ((18)F-FDG) PET/CT has not been shown to offer additional benefit in the initial diagnosis of pancreatic cancer, but studies show benefit of (18)F-FDG PET/CT in initial staging and patient prognosis. There is evidence for (18)F-F
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::f52a6d9346e9f84e26757c00e71c272b
https://pubmed.ncbi.nlm.nih.gov/26099670
https://pubmed.ncbi.nlm.nih.gov/26099670
Publikováno v:
PET-CT and PET-MRI in Oncology ISBN: 9783642011382
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5ce3db7eaf55b445f6d42402998e789a
https://doi.org/10.1007/174_2012_603
https://doi.org/10.1007/174_2012_603